U.S. patent application number 17/744767 was filed with the patent office on 2022-09-01 for mapping binned medical data.
This patent application is currently assigned to Navix International Limited. The applicant listed for this patent is Navix International Limited. Invention is credited to Shlomo BEN-HAIM, Eli DICHTERMAN.
Application Number | 20220277420 17/744767 |
Document ID | / |
Family ID | |
Filed Date | 2022-09-01 |
United States Patent
Application |
20220277420 |
Kind Code |
A1 |
BEN-HAIM; Shlomo ; et
al. |
September 1, 2022 |
MAPPING BINNED MEDICAL DATA
Abstract
A method of generating a combined image of a body part from a
sequence of partially overlapping source images of the body part,
each of the partially overlapping source images showing the body
part at one of a plurality of different times, the source images
being ordered in the sequence according to the different times, the
method including defining a temporally coherent sequence of
transformations, for registering the partially overlapping source
images in the sequence with each other, registering the source
images to each other using the defined temporally coherent sequence
of transformations, to obtain co-registered images, and combining
at least some of the co-registered images into a combined image.
Related apparatus and methods are also described.
Inventors: |
BEN-HAIM; Shlomo; (Geneva,
CH) ; DICHTERMAN; Eli; (Haifa, IL) |
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Applicant: |
Name |
City |
State |
Country |
Type |
Navix International Limited |
Road Town |
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VG |
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Assignee: |
Navix International Limited
Road Town
VG
|
Appl. No.: |
17/744767 |
Filed: |
May 16, 2022 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16971336 |
Aug 20, 2020 |
11334965 |
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PCT/IB2019/051423 |
Feb 21, 2019 |
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17744767 |
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62633119 |
Feb 21, 2018 |
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International
Class: |
G06T 3/40 20060101
G06T003/40; G06T 7/55 20060101 G06T007/55; G06T 7/38 20060101
G06T007/38; G06T 7/00 20060101 G06T007/00 |
Claims
1-16. (canceled)
17. A method of generating an image of a moving body part, the
method comprising: receiving a stream of measurements, each
indicative of a structure of a respective portion of the body part,
the indications of structure being partially overlapping in their
respective portions; binning the stream of measurements to a
sequence of bins, each bin including a set of measurements taken
during a different time window, the time window including a period
also included in a time window of another bin in the sequence, such
that the time windows are partially overlapping in time;
generating, from the sequence of bins, a sequence of source images
of said body part, each said source image imaging a region also
imaged by another image in the sequence, such that the source
images are partially overlapping; and generating from said sequence
of partially overlapping images a combined image.
18. The method of claim 17, comprising: classifying the stream of
measurements to two or more groups of measurements, each group
corresponding to a different movement mode of the body part; and
for at least one of the groups: binning the measurements to a
sequence of bins, each including a set of measurements taken in a
different time window, generating, from the sequence of bins, a
sequence of partially overlapping source images of said body part,
and generating a combined image from the source images.
19. The method of claim 18, wherein said binning, generating a
sequence of partially overlapping source images, and generating a
combined image, is carried out for two or more of the groups, to
generate two or more combined images.
20. The method of claim 19, further comprising registering the two
or more combined images to each other.
21. The method of claim 17, wherein the generating the combined
image comprises: defining a temporally coherent sequence of
transformations, for registering the partially overlapping source
images in the sequence with each other; registering the partially
overlapping source images to each other using the defined
temporally coherent sequence of transformations, to obtain
co-registered images; and combining at least some of the
co-registered images into a combined image.
22. The method of claim 18, wherein said body part is a heart or a
portion thereof, and the movement modes comprise a cardiac rhythm
selected from a sinusoidal beat, and atrial fibrillation.
23. The method of claim 17, further comprising: bringing an
intra-body probe into the body part or to a vicinity thereof;
receiving measurements from the intra-body probe; and generating
the sequence of partially overlapping source images based on the
measurements received from the intra-body probe.
24. A non-transient computer-readable medium containing program
instructions for causing a computer to perform the method of claim
17.
25. A method of generating a movie of a beating heart, the method
comprising: receiving a sequence of images of said beating heart,
each image including a portion representing a region of the heart
also represented in a portion of another image such that the images
are overlapping, and each image based on data collected during a
different time window, the images being ordered in the sequence
according to a time order of the time windows; generating a single
movie frame for each one of the images; and ordering the single
movie frames according to the ordering of the images in the
sequence of images to obtain the movie; wherein generating the
single movie frame for each one of the images comprises: setting
said one of the images to be a master image, and the rest of the
images to be non-master images, defining a temporally coherent
sequence of transformations, each registering a corresponding
non-master image to the master image, transforming each non-master
image according to the transformation defined therefor to obtain a
corresponding transformed image, and combining the transformed
images and the master image into the single movie frame for said
one of the images.
26. The method of claim 25, wherein a difference between any two
transformations defined for two consecutive images is spatially
coherent.
27. The method of claim 25, wherein each of the transformations
defined is spatially coherent.
28. A non-transient computer readable medium containing program
instructions for causing a computer to perform the method of claim
25.
29. A system configured to carry out a method of generating an
image of a moving body part, the system comprising a memory storing
instructions and a processor, instructed by the instructions to:
receive a stream of measurements, each indicative of a structure of
a respective portion of the body part, the indications of structure
being partially overlapping in their respective portions; bin the
stream of measurements to a sequence of bins, each bin including a
set of measurements taken during a different time window, the time
window including a period also included in a time window of another
bin in the sequence, such that the time windows are partially
overlapping in time; generate, from the sequence of bins, a
sequence of source images of said body part, each said source image
imaging a region also imaged by another image in the sequence, such
that the source images are partially overlapping; and generate from
said sequence of partially overlapping images a combined image.
30. The system of claim 29, wherein the processor is further
instructed to: classify the stream of measurements to two or more
groups of measurements, each group corresponding to a different
movement mode of the body part; and for at least one of the groups:
bin the measurements to a sequence of bins, each including a set of
measurements taken in a different time window, generate, from the
sequence of bins, a sequence of partially overlapping source images
of said body part, and generate a combined image from the source
images.
31. The system of claim 30, wherein the processor is instructed to
bin, generate a sequence of partially overlapping source images,
and generate a combined image, for two or more of the groups, to
generate two or more combined images.
32. The system of claim 31, wherein the processor is instructed to
register the two or more combined images to each other.
33. A system configure to generate a movie of a beating heart, the
system comprising a memory storing instructions and a processor,
instructed by the instructions to: receive a sequence of images of
said beating heart, each image including a portion representing a
region of the heart also represented in a portion of another image
such that the images are overlapping, and each image based on data
collected during a different time window, the images being ordered
in the sequence according to a time order of the time windows;
generate a single movie frame for each one of the images; and order
the single movie frames according to the ordering of the images in
the sequence of images to obtain the movie; wherein, to generate
each single movie frame the processor is instructed to: set said
one of the images to be a master image, and the rest of the images
to be non-master images, define a temporally coherent sequence of
transformations, each registering a corresponding non-master image
to the master image, transform each non-master image according to
the transformation defined therefor to obtain a corresponding
transformed image, and combine the transformed images and the
master image into the single movie frame for said one of the
images.
34. The system of claim 33, wherein a difference between any two
transformations defined for two consecutive images is spatially
coherent.
35. The system of claim 33, wherein each of the transformations
defined is spatially coherent.
Description
RELATED APPLICATIONS
[0001] This application is continuation of U.S. patent application
Ser. No. 16/971,336 filed on Aug. 20, 2020, which is a National
Phase of PCT Patent Application No. PCT/IB2019/051423 having
International Filing Date of Feb. 21, 2019, which claims the
benefit of priority under 35 USC .sctn. 119(e) of U.S. Provisional
Patent Application No. 62/633,119 filed on Feb. 21, 2018. The
contents of the above applications are all incorporated by
reference as if fully set forth herein in their entirety.
FIELD AND BACKGROUND OF THE INVENTION
[0002] The present invention, in some embodiments thereof, relates
to transforming medical data captured under different circumstances
to a common framework, and, more particularly, but not exclusively,
to transforming values of data points obtained from an intra-body
probe to a common coordinate system in order to use the data points
to image and/or model anatomical structure.
[0003] Some embodiments of the present invention include modelling
a structure of a body organ or portion thereof based on data
received from a probe when there is mutual movement between the
probe and the body organ portion to be modelled.
[0004] Some embodiments of the present invention include
improvement of modelling a structure of a body organ or portion
thereof based on using data received from a probe when there is
mutual movement between the probe and the body organ portion to be
modelled.
[0005] Embodiments of the invention may be practiced in, for
example, modelling and/or imaging of cardiac structure.
[0006] Background art includes:
[0007] an article titled "A robust detection algorithm to identify
breathing peaks in respiration signals from spontaneously breathing
subjects", published in 2015 Computing in Cardiology Conference,
DOI: 10.1109/CIC.2015.7408645;
[0008] an article titled "Registration of Multiple Temporally
Related Point Sets Using a Novel Variant of the Coherent Point
Drift Algorithm: Application to Coronary Tree Matching" Conference
Paper in Proceedings of SPIE--The International Society for Optical
Engineering, 8669:86690M March 2013 DOI: 10.1117/12.2004764;
[0009] an article titled "A real-time atrial fibrillation detection
algorithm based on the instantaneous state of heart rate",
published in PLoS ONE 10(9) e0136544,
[0010] an article titled "Point Set Registration: Coherent Point
Drift", published on 15 May 2009 on the world-wide-web, in
arxiv(dot)org/abs/0905.2635`, and
[0011] an article titled "Registration of multiple temporally
related point sets using a novel variant of the coherent point
drift algorithm: application to coronary tree matching" published
in Proc. of SPIE vol. 8669.
[0012] The disclosures of all references mentioned above and
throughout the present specification, are hereby incorporated
herein by reference.
SUMMARY OF THE INVENTION
[0013] The present invention, in some embodiments thereof, relates
to transforming medical data captured under different circumstances
to use a common framework, and more particularly, but not
exclusively, to transforming electrical readings obtained from an
intra-body probe to use a common framework coordinate system in
order to use the electrical readings to map and/or image and/or
model anatomical structure.
[0014] Some embodiments of the present invention include modelling
a structure of a body organ or portion thereof based on data
received from a probe when there is mutual movement between the
probe and the body organ portion to be modelled.
[0015] Some embodiments of the present invention include
improvement of modelling a structure of a body organ or portion
thereof based on using data received from a probe when there is
mutual movement between the probe and the body organ portion to be
modelled.
[0016] According to an aspect of some embodiments of the present
invention there is provided a method for imaging of a body organ
undergoing periodic changes in at least one dimension, the method
including measuring at least two partial data sets of the body
organ, determining at least one corresponding data point in each
one of the at least two partial data sets describing the at least
one dimension of the body organ which is undergoing repetitive
changes, projecting at least one of the two partial data sets into
a data set having a common framework, based on the corresponding
data.
[0017] According to some embodiments of the invention, the
projecting at least one of the two partial data sets into a data
set having a common framework includes projecting at least one of
the two partial data sets into another one of the two partial data
sets, based on the corresponding data.
[0018] According to some embodiments of the invention, the
measuring at least two partial data sets of the body organ is
performed during different time periods.
[0019] According to some embodiments of the invention, the
measuring at least two partial data sets of the body organ is
performed during partially-overlapping time periods.
[0020] According to some embodiments of the invention, the
measuring at least two partial data sets of the body organ is
performed at adjacent or partially overlapping locations of the
body organ.
[0021] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on sensor readings, the method including receiving
sensor readings from a plurality of sensors, converting the sensor
readings to data points, classifying each one of the data points to
as belonging to one of a plurality of data bins, identifying a set
of corresponding data points in at least a first data bin and a
second data bin of the plurality of data bins, calculating a
transformation from the corresponding data points in the second
data bin to the corresponding data points in the first data bin,
projecting data points in the second data bin to data points in the
first data bin using the transformation, producing a combined set
of data points including the data points of the first data bin and
the projected data points from the second data bin, and imaging the
combined set of data points.
[0022] According to some embodiments of the invention, the sensors
include electrodes and the sensor readings include electrical
readings.
[0023] According to some embodiments of the invention, converting
the electrical readings to data points includes converting from
values of electrical readings to location values in space.
[0024] According to some embodiments of the invention, the
anatomical structure includes a heart chamber.
[0025] According to some embodiments of the invention, receiving
electrical readings includes receiving measurement from a plurality
of electrodes on an intra-body probe.
[0026] According to some embodiments of the invention, receiving
electrical reading includes receiving measurement from a plurality
of electrodes on an intra-body probe and from at least one body
surface electrode.
[0027] According to some embodiments of the invention, classifying
the data points to a plurality of data bins produces a sparse data
set in at least one of the data bins.
[0028] According to some embodiments of the invention, the
classifying the data points to a plurality of data bins produces a
sparse data set in each one of the data bins.
[0029] According to some embodiments of the invention, a number of
data points in the combined set of data points is greater than a
number of data points in the first data bin.
[0030] According to some embodiments of the invention, the
receiving, the classifying, the identifying, the calculating, the
projecting and the producing a combined set of data points is
performed for more than two data bins.
[0031] According to some embodiments of the invention, the
converting is from electrical readings to dielectric values.
[0032] According to some embodiments of the invention, receiving
sensor readings further includes receiving physical measurements
selected from a group consisting of electric potential, electric
current, electric permittivity, time, location, pressure, blood
pressure, nasal air flow, blood chemical concentration, and
temperature.
[0033] According to some embodiments of the invention, the data
points include a dimension selected from a group consisting of
time, location in space, pressure, temperature, phase in cardiac
cycle, phase in breathing cycle, amplitude of breathing motion,
category of cardiac rhythm, phase in cycle of adjacent heart
chamber, and category of breathing type.
[0034] According to some embodiments of the invention, the second
data bin belongs to a same dimension as the first data bin.
[0035] According to some embodiments of the invention, the second
data bin belongs to a different dimension than the first data
bin.
[0036] According to some embodiments of the invention, the
transformation includes a transformation from a data bin including
data points of a chaotic cardiac rhythm to a data bin including
data points of a non-chaotic cardiac rhythm.
[0037] According to some embodiments of the invention, the
classifying each one of the data points to as belonging to one of a
plurality of data bins includes classifying at least some of the
data points as belonging to at least one atrial fibrillation (AF)
data bin.
[0038] According to some embodiments of the invention, the
classifying each one of the data points to as belonging to one of a
plurality of data bins includes classifying at least some of the
data points as belonging to at least one arrhythmia data bin.
[0039] According to some embodiments of the invention, the
transformation includes a transformation from a data bin including
data points of a cardiac rhythm classified as atrial fibrillation
(AF) to a data bin including data points of a non-AF cardiac
rhythm.
[0040] According to some embodiments of the invention, the
transformation includes a plurality of transformations selected
from a group consisting of (a) a transformation from a data bin
including data points of a first cardiac rhythm category to a data
bin including data points of a second cardiac rhythm category, (b)
a transformation from a data bin including data points of a first
breathing rhythm category to a data bin including data points of a
second breathing rhythm category, and (c) a transformation from a
data bin including data points of a first cardiac rhythm category
to a data bin including data points of a second cardiac rhythm
category.
[0041] According to some embodiments of the invention, the
transformation includes a sequence of transformations starting with
transformation (a), then (b), then (c).
[0042] According to some embodiments of the invention, the combined
set of data points includes less dimensions than a number of
dimensions of the data points of a combination of the data points
of the first data bin and the data points of the second data
bin.
[0043] According to some embodiments of the invention, the
transformation includes a multi-dimensional scaling (MDS)
transformation.
[0044] According to some embodiments of the invention, the
transformation includes a non-rigid transformation.
[0045] According to some embodiments of the invention, the
transformation includes a rigid transformation.
[0046] According to some embodiments of the invention, the
transformation includes a Coherent Point Drift (CPD)
transformation.
[0047] According to some embodiments of the invention, the CPD
transformation is based on identifying the set of corresponding
data points in at least the first data bin and the second data bin
of the plurality of data bins.
[0048] According to some embodiments of the invention, the
transformation includes best-fit transformation.
[0049] According to some embodiments of the invention, the
transformation further includes imposing spatial coherence on the
transformed measurements.
[0050] According to some embodiments of the invention, the
transformation further includes imposing temporal coherence on the
transformed measurements.
[0051] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
measurement component for receiving measurements from a plurality
of electrodes, a processing component for classifying the
measurements to a plurality of data bins, and a mapping component
for identifying a set of corresponding data points in at least a
first data bin and a second data bin of the plurality of data bins,
calculating a transformation from the corresponding data points in
the second data bin to the corresponding data points in the first
data bin, projecting data points in the second data bin to data
points in the first data bin using the transformation, producing a
combined set of data points including the data points of the first
data bin and the projected data points from the second data
bin.
[0052] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving electrical readings from a plurality of electrodes,
converting the electrical readings to data points, classifying each
one of the data points as belonging to one of a plurality of data
bins, identifying a set of corresponding data points in at least a
first data bin and a second data bin of the plurality of data bins,
projecting data points in the second data bin to data points in the
first data bin using a transformation, producing a combined set of
data points including the data points of the first data bin and the
projected data points from the second data bin, and imaging the
combined set of data points.
[0053] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving electrical readings from a
plurality of electrodes, a processing component for converting the
electrical readings to data points, a classifying component for
classifying each one of the data points as belonging to one of a
plurality of data bins, an identifying component for identifying
correspondence of a set of data points in at least a first data bin
and a second data bin of the plurality of data bins, a projecting
component for projecting data points in the second data bin to data
points in the first data bin using a transformation, a combining
component for producing a combined set of data points including the
data points of the first data bin and the projected data points
from the second data bin, and an imaging component for producing an
image from the combined set of data points. Producing an image may
include converting data into a format suitable for display. In some
embodiments the apparatus includes a display for displaying the
image.
[0054] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving data points measured from a plurality of electrodes,
classifying each one of the data points as belonging to one of a
plurality of data bins, identifying a set of corresponding data
points in at least a first data bin and a second data bin of the
plurality of data bins, projecting data points in the second data
bin to data points in the first data bin using a transformation,
producing a combined set of data points including the data points
of the first data bin and the projected data points from the second
data bin, and imaging the combined set of data points.
[0055] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving data points measured from a
plurality of electrodes, a classifying component for classifying
each one of the data points as belonging to one of a plurality of
data bins, an identifying component for identifying a set of
corresponding data points in at least a first data bin and a second
data bin of the plurality of data bins, a projecting component for
projecting data points in the second data bin to data points in the
first data bin using a transformation, a combining component for
producing a combined set of data points including the data points
of the first data bin and the projected data points from the second
data bin, and an imaging component for producing an image from the
combined set of data points, e.g., by converting the data points
into a format suitable for display. In some embodiments the
apparatus includes a display for displaying the image.
[0056] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving electrical readings from a plurality of electrodes,
converting the electrical readings to data points, classifying each
one of the data points as belonging to one of a plurality of data
bins, projecting data points in a second data bin to data points in
a first data bin using a transformation, producing a combined set
of data points including the data points of the first data bin and
the projected data points from the second data bin, and imaging the
combined set of data points.
[0057] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving electrical readings from a
plurality of electrodes, a processing component for converting the
electrical readings to data points, a classifying component for
classifying each one of the data points as belonging to one of a
plurality of data bins, a projecting component for projecting data
points in a second data bin to data points in a first data bin
using a transformation, a combining component for producing a
combined set of data points including the data points of the first
data bin and the projected data points from the second data bin,
and an imaging component for producing an image from the combined
set of data points. In some embodiments the apparatus includes a
display for displaying the image. Here, and in other embodiments
that include an imaging component and a display, the imaging
component preferably produces the image in a format suitable for
display on that display.
[0058] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving data points measured from a plurality of electrodes,
classifying each one of the data points as belonging to one of a
plurality of data bins, projecting data points in a second data bin
to data points in a first data bin using a transformation,
producing a combined set of data points including the data points
of the first data bin and the projected data points from the second
data bin, and imaging the combined set of data points.
[0059] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving data points measured from a
plurality of electrodes, a classifying component for classifying
each one of the data points as belonging to one of a plurality of
data bins, a projecting component for projecting data points in a
second data bin to data points in a first data bin using a
transformation, a combining component for producing a combined set
of data points including the data points of the first data bin and
the projected data points from the second data bin, and an imaging
component for producing an image from the combined set of data
points. In some embodiments the apparatus includes a display for
displaying the image produced by the imaging component.
[0060] According to an aspect of some embodiments of the present
invention there is provided a method of generating a combined image
of a body part from a sequence of partially overlapping source
images of the body part, each of the partially overlapping source
images showing the body part at one of a plurality of different
times, the source images being ordered in the sequence according to
the different times, the method including defining a temporally
coherent sequence of transformations, for registering the partially
overlapping source images in the sequence with each other,
registering the source images to each other using the defined
temporally coherent sequence of transformations, to obtain
co-registered images, and combining at least some of the
co-registered images into a combined image.
[0061] According to some embodiments of the invention, the body
part undergoes a periodic change, and the source images are ordered
in the sequence according to their phase in a cycle of the periodic
change.
[0062] According to some embodiments of the invention, the method
includes setting one of the source images to be a master image, and
the rest of the source images to be non-master images, defining for
the non-master images, a temporally coherent sequence of
transformations, each transformation registering a respective
non-master image to the master image, transforming each non-master
image, using the transformation defined for the non-master image,
to obtain a corresponding transformed image, and combining at least
some of the transformed images and the master image into a single
combined image.
[0063] According to some embodiments of the invention, a difference
between any two transformations defined for two consecutive source
images is spatially coherent.
[0064] According to some embodiments of the invention, each
transformation of the temporally coherent sequence of
transformations is spatially coherent.
[0065] According to some embodiments of the invention, the
temporally coherent sequence of transformations is defined using a
cost function penalizing for spatial incoherence of a
transformation in the sequence.
[0066] According to some embodiments of the invention, the
temporally coherent sequence of transformations is defined using a
cost function penalizing for spatial incoherence of a difference
between sequential transformations in the sequence.
[0067] According to some embodiments of the invention, each one of
the source images in the sequence shows the body part as imaged
during a different time window, and time windows of at least some
of the source images in the sequence partially overlap.
[0068] According to some embodiments of the invention, time windows
of each two consecutive source images in the sequence partially
overlap.
[0069] According to some embodiments of the invention, each one of
the source images includes points representing values of electrical
measurements, and the method further includes transforming the
combined image into a transformed combined image including points
representing locations in space.
[0070] According to some embodiments of the invention, each one of
the source images in the sequence includes points representing
locations in space.
[0071] According to some embodiments of the invention, each one of
the source images is a point cloud, and the combining the
co-registered images produces a combined point cloud, and further
including reconstructing the combined image from the combined point
cloud.
[0072] According to some embodiments of the invention, the
reconstructing the combined image from the combined point cloud
includes using a ball pivoting algorithm.
[0073] According to some embodiments of the invention, a specified
location is marked on a plurality of the source images, and the
transformations are defined to transform the location marked on the
plurality of the source images to a same location.
[0074] According to some embodiments of the invention, the method
further includes bringing an intra-body probe into the body part or
to a vicinity thereof, receiving measurements from the intra-body
probe, and generating the sequence of partially overlapping source
images based on the measurements received from the intra-body
probe.
[0075] According to an aspect of some embodiments of the present
invention there is provided a non-transient computer readable
medium containing program instructions for causing a computer to
perform the method of any one of the above methods.
[0076] According to an aspect of some embodiments of the present
invention there is provided a method of generating an image of a
moving body part, the method including receiving a stream of
measurements indicative of structure of partially overlapping
portions of the body part, binning the stream of measurements to a
sequence of bins, each bin including a set of measurements taken
during a different time window, the time window partially
overlapping with a time window of a sequential bin, generating,
from the sequence of bins, a sequence of partially overlapping
source images of the body part, and generating from the sequence of
partially overlapping images a combined image.
[0077] According to some embodiments of the invention, classifying
the stream of measurements to two or more groups of measurements,
each group corresponding to a different movement mode of the body
part, and for at least one of the groups binning the measurements
to a sequence of bins, each including a set of measurements taken
in a different time window, generating, from the sequence of bins,
a sequence of partially overlapping source images of the body part,
and generating a combined image from the source images.
[0078] According to some embodiments of the invention, the binning,
generating a sequence of partially overlapping source images, and
generating a combined image, is carried out for two or more of the
groups, to generate two or more combined images.
[0079] According to some embodiments of the invention, the method
includes registering the two or more combined images to each
other.
[0080] According to some embodiments of the invention, the
generation of the combined image is by a method according to any
one of the above-mentioned methods.
[0081] According to some embodiments of the invention, the body
part is a heart or a portion thereof, and the movement modes
include a cardiac rhythm selected from a sinusoidal beat, and
atrial fibrillation.
[0082] According to some embodiments of the invention, the method
further includes bringing an intra-body probe into the body part or
to a vicinity thereof, receiving measurements from the intra-body
probe, and generating the sequence of partially overlapping source
images based on the measurements received from the intra-body
probe.
[0083] According to an aspect of some embodiments of the present
invention there is provided a non-transient computer readable
medium containing program instructions for causing a computer to
perform any one of the above methods.
[0084] According to an aspect of some embodiments of the present
invention there is provided a method of generating a movie of a
beating heart, the method including receiving a sequence of
partially overlapping images of the beating heart, each image based
on data collected during a different time window, the images being
ordered in the sequence according to a time order of the time
windows, generating a single movie frame for each one of the
images, and ordering the single movie frames according to the
ordering of the images in the sequence of images to obtain the
movie, wherein generating a single movie frame for each one of the
images includes setting the one of the images to be a master image,
and the rest of the images to be non-master images, defining a
temporally coherent sequence of transformations, each registering a
corresponding non-master image to the master image, transforming
each non-master image according to the transformation defined
therefor to obtain a corresponding transformed image, combining the
transformed images and the master image into the single movie frame
for the one of the images.
[0085] According to some embodiments of the invention, a difference
between any two transformations defined for two consecutive images
is spatially coherent.
[0086] According to some embodiments of the invention, each of the
transformations defined is spatially coherent.
[0087] According to an aspect of some embodiments of the present
invention there is provided a non-transient computer readable
medium containing program instructions for causing a computer to
perform any one of the above-mentioned method.
[0088] According to an aspect of some embodiments of the present
invention there is provided a system configured to carry out any
one of the above-mentioned methods.
[0089] According to an aspect of some embodiments of the present
invention there is provided a method for combining data sets, each
indicative of a structure of a body organ, the method including
receiving two data sets, each data set including information
indicative of a structure of the body organ, wherein at least some
data points in each set are indicative of structure of a same
portion of the body organ, determining a first data point in each
one of the two data sets, the first data points being indicative of
the structure of the same portion of the body organ, and projecting
a first one of the two data sets into a data set having a common
coordinate system with a second one of the two data sets, based on
the first data points determined in each one of the two data
sets.
[0090] According to some embodiments of the invention, the
projecting the first one of the two data sets into a data set
having a common coordinate system includes projecting the first one
of the two data sets into the second one of the two data sets.
[0091] According to some embodiments of the invention, at least
some data in the two data sets was measured during
partially-overlapping time periods.
[0092] According to an aspect of some embodiments of the present
invention there is provided a method of imaging an anatomical
structure based on sensor readings, the method including receiving
sensor readings from a plurality of sensors, converting the sensor
readings to data points, classifying each one of the data points as
belonging to one of a plurality of data bins, identifying a first
set of data points in a first data bin and a second set of data
points in a second data bin of the plurality of data bins, each
point in the first set corresponding to a point in the second set,
calculating a transformation from the second set of data points to
the first set of data points, projecting data points in the second
data bin to data points in the first data bin using the
transformation, producing a combined set of data points including
the data points of the first data bin and the projected data points
from the second data bin, and imaging the anatomical structure
based on data included in the combined set of data points.
[0093] According to some embodiments of the invention, the sensors
include electrodes, the sensor readings include electrical
readings, and converting the electrical readings to data points
includes converting from values of electrical readings to location
values in space.
[0094] According to some embodiments of the invention, the
anatomical structure includes a heart chamber.
[0095] According to some embodiments of the invention, receiving
electrical reading includes receiving measurements from a plurality
of electrodes on an intra-body probe and from at least one body
surface electrode.
[0096] According to some embodiments of the invention, receiving
sensor readings further includes receiving measurements selected
from a group consisting of electric potential, electric current,
electric permittivity, time, location, pressure, blood pressure,
nasal air flow, blood chemical composition, and temperature.
[0097] According to some embodiments of the invention, the data
points include a dimension selected from a group consisting of
time, location in space, pressure, temperature, phase in cardiac
cycle, phase in breathing cycle, amplitude of breathing motion,
category of cardiac rhythm, phase in cycle of adjacent heart
chamber, and category of breathing type.
[0098] According to some embodiments of the invention, the
classifying each one of the data points as belonging to one of a
plurality of data bins includes classifying at least some of the
data points as belonging to at least one data bin selected from a
group consisting of an atrial fibrillation (AF) data bin, an
arrhythmia data bin.
[0099] According to some embodiments of the invention, the
transformation includes a transformation from a data bin including
data points of a cardiac rhythm classified as atrial fibrillation
(AF) to a data bin including data points of a non-AF cardiac
rhythm.
[0100] According to some embodiments of the invention, the
transformation includes a transformation selected from a group
consisting of (a) a transformation from a data bin including data
points of a first cardiac rhythm category to a data bin including
data points of a second cardiac rhythm category, (b) a
transformation from a data bin including data points of a first
breathing rhythm category to a data bin including data points of a
second breathing rhythm category, and (c) a transformation from a
data bin including data points of a first cardiac rhythm category
to a data bin including data points of a second cardiac rhythm
category.
[0101] According to some embodiments of the invention, the
transformation includes a transformation selected from a group
consisting of a multi-dimensional scaling (MDS) transformation, a
non-rigid transformation, a rigid transformation, a Coherent Point
Drift (CPD) transformation, and a best-fit transformation.
[0102] According to some embodiments of the invention, the
transformation further includes imposing spatial coherence on the
transformed measurements.
[0103] According to some embodiments of the invention, the
transformation further includes imposing temporal coherence on the
transformed measurements.
[0104] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including an
intra-body electrode, a measurement component configured to receive
measurements from the intra-body electrode, a processor configured
to classify the measurements to a plurality of data bins, and a
mapping component configured to identify a set of corresponding
data points in at least a first data bin and a second data bin of
the plurality of data bins, calculate a transformation from the
corresponding data points in the second data bin to the
corresponding data points in the first data bin, project data
points in the second data bin to data points in the first data bin
using the transformation, and produce a combined set of data points
including the data points of the first data bin and the projected
data points from the second data bin.
[0105] According to an aspect of some embodiments of the present
invention there is provided a method of imaging an anatomical
structure based on electrical readings, the method including
receiving electrical readings from a plurality of electrodes,
converting the electrical readings to data points, classifying each
one of the data points as belonging to one of a plurality of data
bins, identifying a set of corresponding data points in at least a
first data bin and a second data bin of the plurality of data bins,
projecting data points in the second data bin to data points in the
first data bin using a transformation, producing a combined set of
data points including the data points of the first data bin and the
projected data points from the second data bin, and imaging the
anatomical structure based on data included in the combined set of
data points.
[0106] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including an
intra-body electrode, a data input component configured to receive
electrical readings from the intra-body electrode, a processing
component configured to convert the electrical readings to data
points, a classifying component configured to classify each one of
the data points as belonging to one of a plurality of data bins, an
identifying component configured to identify correspondence of a
set of data points in at least a first data bin and a second data
bin of the plurality of data bins, a projecting component
configured to project data points in the second data bin to data
points in the first data bin using a transformation, a combining
component configured to produce a combined set of data points
including the data points of the first data bin and the projected
data points from the second data bin, and an imaging component
configured to image the combined set of data points.
[0107] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving data points measured from a plurality of electrodes,
classifying each one of the data points as belonging to one of a
plurality of data bins, identifying a set of corresponding data
points in at least a first data bin and a second data bin of the
plurality of data bins, projecting data points in the second data
bin to data points in the first data bin using a transformation,
producing a combined set of data points including the data points
of the first data bin and the projected data points from the second
data bin, and imaging the anatomical structure based on data
included in the combined set of data points.
[0108] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving data points measured from a
plurality of electrodes, a classifying component for classifying
each one of the data points as belonging to one of a plurality of
data bins, an identifying component for identifying a set of
corresponding data points in at least a first data bin and a second
data bin of the plurality of data bins, a projecting component for
projecting data points in the second data bin to data points in the
first data bin using a transformation, a combining component for
producing a combined set of data points including the data points
of the first data bin and the projected data points from the second
data bin, and an imaging component for imaging the combined set of
data points.
[0109] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving electrical readings from a plurality of electrodes,
converting the electrical readings to data points, classifying each
one of the data points as belonging to one of a plurality of data
bins, projecting data points in a second data bin to data points in
a first data bin using a transformation, producing a combined set
of data points including the data points of the first data bin and
the projected data points from the second data bin, and imaging the
combined set of data points.
[0110] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving electrical readings from a
plurality of electrodes, a processing component for converting the
electrical readings to data points, a classifying component for
classifying each one of the data points as belonging to one of a
plurality of data bins, a projecting component for projecting data
points in a second data bin to data points in a first data bin
using a transformation, a combining component for producing a
combined set of data points including the data points of the first
data bin and the projected data points from the second data bin,
and an imaging component for imaging the combined set of data
points.
[0111] According to an aspect of some embodiments of the present
invention there is provided a method for imaging an anatomical
structure based on electrical readings, the method including
receiving data points measured from a plurality of electrodes,
classifying each one of the data points as belonging to one of a
plurality of data bins, projecting data points in a second data bin
to data points in a first data bin using a transformation,
producing a combined set of data points including the data points
of the first data bin and the projected data points from the second
data bin, and imaging the combined set of data points.
[0112] According to an aspect of some embodiments of the present
invention there is provided apparatus for imaging an anatomical
structure based on electrical readings, the apparatus including a
data input component for receiving data points measured from a
plurality of electrodes, a classifying component for classifying
each one of the data points as belonging to one of a plurality of
data bins, a projecting component for projecting data points in a
second data bin to data points in a first data bin using a
transformation, a combining component for producing a combined set
of data points including the data points of the first data bin and
the projected data points from the second data bin, and an imaging
component for imaging the combined set of data points.
[0113] Unless otherwise defined, all technical and/or scientific
terms used herein have the same meaning as commonly understood by
one of ordinary skill in the art to which the invention pertains.
Although methods and materials similar or equivalent to those
described herein can be used in the practice or testing of
embodiments of the invention, exemplary methods and/or materials
are described below. In case of conflict, the patent specification,
including definitions, will control. In addition, the materials,
methods, and examples are illustrative only and are not intended to
be necessarily limiting.
[0114] As will be appreciated by one skilled in the art, some
embodiments of the present invention may be embodied as a system,
method or computer program product.
[0115] Accordingly, some embodiments of the present invention may
take the form of an entirely hardware embodiment, an entirely
software embodiment (including firmware, resident software,
micro-code, etc.) or an embodiment combining software and hardware
aspects that may all generally be referred to herein as a
"circuit," "module" or "system." Furthermore, some embodiments of
the present invention may take the form of a computer program
product embodied in one or more computer readable medium(s) having
computer readable program code embodied thereon. Implementation of
the method and/or system of some embodiments of the invention can
involve performing and/or completing selected tasks manually,
automatically, or a combination thereof. Moreover, according to
actual instrumentation and equipment of some embodiments of the
method and/or system of the invention, several selected tasks could
be implemented by hardware, by software or by firmware and/or by a
combination thereof, e.g., using an operating system.
[0116] For example, hardware for performing selected tasks
according to some embodiments of the invention could be implemented
as a chip or a circuit. As software, selected tasks according to
some embodiments of the invention could be implemented as a
plurality of software instructions being executed by a computer
using any suitable operating system. In an exemplary embodiment of
the invention, one or more tasks according to some exemplary
embodiments of method and/or system as described herein are
performed by a data processor, such as a computing platform for
executing a plurality of instructions. Optionally, the data
processor includes a volatile memory for storing instructions
and/or data and/or a non-volatile storage, for example, a magnetic
hard-disk and/or removable media, for storing instructions and/or
data. Optionally, a network connection is provided as well. A
display and/or a user input device such as a keyboard or mouse are
optionally provided as well.
[0117] Any combination of one or more computer readable medium(s)
may be utilized for some embodiments of the invention. The computer
readable medium may be a computer readable signal medium or a
computer readable storage medium. A computer readable storage
medium may be, for example, but not limited to, an electronic,
magnetic, optical, electromagnetic, infrared, or semiconductor
system, apparatus, or device, or any suitable combination of the
foregoing. More specific examples (a non-exhaustive list) of the
computer readable storage medium would include the following: an
electrical connection having one or more wires, a portable computer
diskette, a hard disk, a random access memory (RAM), a read-only
memory (ROM), an erasable programmable read-only memory (EPROM or
Flash memory), an optical fiber, a portable compact disc read-only
memory (CD-ROM), an optical storage device, a magnetic storage
device, or any suitable combination of the foregoing. In the
context of this document, a computer readable storage medium may be
any tangible medium that can contain, or store a program for use by
or in connection with an instruction execution system, apparatus,
or device.
[0118] A computer readable signal medium may include a propagated
data signal with computer readable program code embodied therein,
for example, in baseband or as part of a carrier wave. Such a
propagated signal may take any of a variety of forms, including,
but not limited to, electro-magnetic, optical, or any suitable
combination thereof. A computer readable signal medium may be any
computer readable medium that is not a computer readable storage
medium and that can communicate, propagate, or transport a program
for use by or in connection with an instruction execution system,
apparatus, or device.
[0119] Program code embodied on a computer readable medium and/or
data used thereby may be transmitted using any appropriate medium,
including but not limited to wireless, wireline, optical fiber
cable, RF, etc., or any suitable combination of the foregoing.
[0120] Computer program code for carrying out operations for some
embodiments of the present invention may be written in any
combination of one or more programming languages, including an
object oriented programming language such as Java, Smalltalk, C++
or the like and conventional procedural programming languages, such
as the "C" programming language or similar programming languages.
The program code may execute entirely on the user's computer,
partly on the user's computer, as a stand-alone software package,
partly on the user's computer and partly on a remote computer or
entirely on the remote computer or server. In the latter scenario,
the remote computer may be connected to the user's computer through
any type of network, including a local area network (LAN) or a wide
area network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider).
[0121] Some embodiments of the present invention may be described
below with reference to flowchart illustrations and/or block
diagrams of methods, apparatus (systems) and computer program
products according to embodiments of the invention. It will be
understood that each block of the flowchart illustrations and/or
block diagrams, and combinations of blocks in the flowchart
illustrations and/or block diagrams, can be implemented by computer
program instructions. These computer program instructions may be
provided to a processor of a general purpose computer, special
purpose computer, or other programmable data processing apparatus
to produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or
blocks.
[0122] These computer program instructions may also be stored in a
computer readable medium that can direct a computer, other
programmable data processing apparatus, or other devices to
function in a particular manner, such that the instructions stored
in the computer readable medium produce an article of manufacture
including instructions which implement the function/act specified
in the flowchart and/or block diagram block or blocks.
[0123] The computer program instructions may also be loaded onto a
computer, other programmable data processing apparatus, or other
devices to cause a series of operational steps to be performed on
the computer, other programmable apparatus or other devices to
produce a computer implemented process such that the instructions
which execute on the computer or other programmable apparatus
provide processes for implementing the functions/acts specified in
the flowchart and/or block diagram block or blocks.
[0124] Some of the methods described herein are generally designed
only for use by a computer, and may not be feasible or practical
for performing purely manually, by a human expert. A human expert,
who wanted to manually perform similar tasks, might be expected to
use completely different methods, e.g., making use of expert
knowledge and/or the pattern recognition capabilities of the human
brain, which would be vastly more efficient than manually going
through the steps of the methods described herein.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
[0125] Some embodiments of the invention are herein described, by
way of example only, with reference to the accompanying drawings
and images. With specific reference now to the drawings and images
in detail, it is stressed that the particulars shown are by way of
example and for purposes of illustrative discussion of embodiments
of the invention. In this regard, the description taken with the
drawings and images makes apparent to those skilled in the art how
embodiments of the invention may be practiced.
[0126] In the drawings:
[0127] FIG. 1 is a simplified line drawing illustration of images
produced of a portion of a heart at two time points according to a
prior art method of imaging;
[0128] FIG. 2 is a simplified line drawing illustration of
transforming data points from one data bin to another data bin, and
using data points from both data bins to produce an image,
according to some embodiments of the invention;
[0129] FIG. 3A is a simplified block diagram illustration of a
system for measuring medical data, classifying and/or binning the
medical data, and transforming the medical data to use a common
framework according to some embodiments of the invention;
[0130] FIG. 3B is a simplified block diagram illustration of a
system for measuring medical data in a first framework and
transforming the medical data to a second framework according to
some embodiments of the invention;
[0131] Each of FIGS. 3C, 3D, 3E, and 3F is a simplified block
diagram illustration of a system for imaging an anatomical
structure based on electrical readings according to some
embodiments of the invention;
[0132] FIG. 4A is a simplified flowchart illustration of a method
for producing a model of a body organ based on electrical readings
according to some embodiments of the invention;
[0133] FIG. 4B is a simplified flowchart illustration of a method
for imaging a patient organ based on electrical readings according
to some embodiments of the invention;
[0134] FIG. 5A is a simplified flowchart illustration of a method
for combining gate-projected data points according to some
embodiments of the invention;
[0135] FIG. 5B is a simplified flowchart illustration of a method
for combining gate-projected data points to produce a combined
image according to some embodiments of the invention;
[0136] FIG. 6A is a simplified flowchart of a method for imaging an
anatomical structure based on electrical readings according to an
exemplary embodiment of the invention;
[0137] FIG. 6B is a simplified flowchart of a method for imaging an
anatomical structure based on electrical readings according to an
exemplary embodiment of the invention;
[0138] FIG. 6C is a simplified flowchart of a method for imaging an
anatomical structure based on electrical readings according to an
exemplary embodiment of the invention;
[0139] FIG. 6D is a simplified flowchart of a method for imaging an
anatomical structure based on electrical readings according to an
exemplary embodiment of the invention;
[0140] FIG. 7A is a graph showing an example effect of
gate-projection on data points according to some embodiments of the
invention;
[0141] FIG. 7B is a graph showing a normal cardiac rhythm and an
abnormal cardiac rhythm differentiated according to some
embodiments of the invention;
[0142] FIG. 8 is a simplified line drawing illustration of methods
of gathering position-identifying information using intra-body
probes according to some embodiments of the invention;
[0143] FIG. 9 is an image of a heart produced following gate
projection of several data bins into one common reference data bin
according to some embodiments of the invention;
[0144] FIG. 10A is a flowchart illustration of a method of
generating an image of a body part according to an exemplary
embodiment of the invention;
[0145] FIG. 10B is a flowchart illustration of a method of
generating an image of a body part according to an exemplary
embodiment of the invention;
[0146] FIG. 11A is a simplified flowchart illustration of a method
of combining N images into one according to an exemplary embodiment
of the invention;
[0147] FIG. 11B is a simplified flowchart illustration of a method
of combining N images into one according to an exemplary embodiment
of the invention;
[0148] FIG. 11C is a simplified flowchart illustration of a method
of generating a combined image of a body part from a sequence of
partially overlapping source images of the body part according to
an exemplary embodiment of the invention;
[0149] FIG. 12 is a simplified flowchart illustration of a method
of generating an image from a stream of data according to an
exemplary embodiment of the invention; and
[0150] FIG. 13 is a simplified flowchart illustration of a method
for producing a movie of a beating heart from a sequence of images
of the beating heart according to an exemplary embodiment of the
invention.
DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION
[0151] The present invention, in some embodiments thereof, relates
to transforming medical data captured under different circumstances
to a common framework, and, more particularly, but not exclusively,
to transforming values of data points obtained from an intra-body
probe to a common coordinate system in order to use the data points
to image and/or model anatomical structure.
[0152] Some embodiments of the present invention include modelling
a structure of a body organ or portion thereof based on data
received from a probe when there is mutual movement between the
probe and the body organ portion to be modelled.
[0153] Some embodiments of the present invention include
improvement of modelling a structure of a body organ or portion
thereof based on using data received from a probe when there is
mutual movement between the probe and the body organ portion to be
modelled.
[0154] The term "image" is used throughout the present
specification and claims to mean a visual representation of a
structure, potentially suitable for display by a display device.
The term "image" when used as a verb--to image--is used throughout
the present specification and claims to mean to produce or generate
an image.
[0155] The term "model" is used throughout the present
specification and claims to mean a data set which includes one or
more data values that represent a structure of one or more
location(s) in a patient's body. The term "model" when used as a
verb--to model--in all its grammatical forms is used throughout the
present specification and claims to mean to produce or generate a
model or to edit data in a model.
[0156] In various embodiments, the medical data optionally includes
values of location (e.g. spatial coordinates), time (e.g. clock
time and/or time along a heartbeat cycle), electrical readings
(e.g. current and/or electric potential values); values computed
based on the electrical readings (e.g. impedance, various other
dielectric properties); and additional physical data (e.g. pH,
color, pressure).
[0157] An example field in which embodiments of the invention may
be practiced is construction of a model of an anatomical structure
(e.g., body cavity). Construction of the model of an anatomical
structure may include mapping data, e.g., electrical readings, to
positions within the structure. In some embodiments an image of the
model of an anatomical structure is optionally made. In some
embodiments the image is optionally displayed.
[0158] In some embodiments, mapping electrical readings to
positions within the structure is performed based on knowing, for
at least some electric readings, to which element or position in
the structure the electrical readings belong. For example, some
locations in a heart are known to provide higher electrical
readings than other locations. One such example is the openings of
the pulmonary veins to the left atrium, where blood is
exceptionally rich in oxygen, and this oxygen content is reflected
in marked impedance values. In some embodiments a transition
between low electrical reading to higher electrical reading is
optionally mapped to a location in the heart where such transition
is known to occur.
[0159] In some embodiments, mapping electrical readings to
locations in the structure is performed based on knowing, for at
least some electric readings, to which location in the structure
the electrical readings belong. For example, some locations in a
heart are known to provide higher electrical readings than other
locations. In some embodiments a transition between low electrical
reading(s) to higher electrical reading(s) is optionally mapped to
a location in the structure where such transition is known to
occur.
[0160] In some embodiments, mapping readings from other sensors to
locations in space is optionally performed based on knowing, for at
least some of the readings from the other sensors, to which
location in space or in the structure the readings belong. For
example, some locations in a body lumen, such as intestines for
example, are known to provide different pH readings than other
locations. In some embodiments a transition between values of pH
reading(s) is optionally mapped to a location in space, or location
in the structure, where such transition is known to occur.
[0161] An example field in which embodiments of the invention may
be practiced is, by way of a non-limiting example, construction of
a model of cardiac structure and/or cardiac imaging. An example
field in which embodiments of the invention may be practiced is
cardiac imaging and/or construction of a model of cardiac
structure, optionally as part of a cardiac ablation procedure.
Introduction
[0162] According to some embodiments, data may be collected at
different times during a medical treatment to compose an image
and/or map and/or construct a model of an anatomical structure
(e.g., a body cavity). As used herein, the language "constructing a
model of an anatomical structure" is used to describe producing a
set of data describing the anatomical structure, optionally in one,
two or three dimensions, optionally including physical attributes
such as conductance, electric potential, color, pH and so on.
[0163] In some embodiments, the model is constructed based on
measurements made at different times, and at different times
different details were observed and/or different measurements were
made. In some such embodiments, a frozen model is made by
registering all the details to a common framework, such as to a
common coordinate system, and then combining the details together
into a frozen model, which includes details measured at different
times. In some embodiments, spatial relationships between details
which were measured only some of the time, are kept in the frozen
model even when a modeled body part deforms during the
measurements. In some embodiments a time of measurement is
associated with the measurements and optionally included in dataset
which contains the measurements.
[0164] As used herein, the language "imaging an anatomical
structure" is used to describe producing an image of the anatomical
structure, optionally in one, two or three dimensions.
[0165] In exemplary embodiments where a set of data is used to
image the anatomical structure, the language "imaging an anatomical
structure" is used to describe producing a set of data suitable for
displaying an image of the anatomical structure, optionally in one,
two or three dimensions, optionally additionally including time in
the set of data.
[0166] In cardiac imaging and/or in using a roving catheter inside
a heart chamber to construct a model of cardiac structure, data may
be collected at different times (e.g., when the catheter roves at
different locations inside the heart) to compose an image and/or
map and/or construct a model of the heart.
[0167] The data may include, inter alia, catheter locations,
locally sensed information (e.g. pressure, voltage, impedance,
activation times, temperature, conduction, etc.) and information
sensed from outside a body. The data collected (i.e. in the
temporal or spatial domains) is optionally used for forming a map
or model of the body cavity; such as a heart chamber.
[0168] Cardiac ablation procedures may include use of catheterized
intra-body ablation probes (for example, RF ablation probes). Such
procedures are performed, for example, in the treatment of cardiac
arrhythmia.
[0169] One form of catheter ablation known as RF ablation relies on
heating caused by interaction between a high-frequency alternating
current (e.g., 350-500 kHz) introduced to a treatment region, and a
dielectric material (e.g., tissue) in the treatment region. One
variable affecting the heating is a frequency-dependent relative
permittivity K of tissue being treated. A (unit-less) relative
permittivity of a material (herein, K or dielectric constant) is a
measure of how the material of the tissue reduces an electrical
field imposed across it (storing and/or dissipating energy of the
electrical field). Relative permittivity is commonly expressed
as
.kappa. = .epsilon. r ( .omega. ) = .epsilon. .function. ( .omega.
) .epsilon. 0 , ##EQU00001##
where .omega.=2.pi.f, and f is the frequency (of an imposed voltage
signal). In general, .epsilon..sub.r(.omega.) is complex valued;
that is:
.epsilon..sub.r(.omega.)=.epsilon.'.sub.r(.omega.)+.epsilon.''.sub.r(.ome-
ga.).
[0170] The real part .epsilon.'.sub.r(.omega.) is a measure of how
energy of an applied electrical field is stored in the tissue (at a
given electrical field frequency), while the imaginary part
.epsilon.''.sub.r (.omega.) is a measure of energy dissipated. It
is this dissipated energy that is converted, for example, into heat
for ablation. Loss in turn is optionally expressed as a sum of
dielectric loss .epsilon.''.sub.rd and conductivity .sigma. as
.epsilon. r '' ( .omega. ) = .epsilon. rd '' + .sigma. .omega.
.epsilon. 0 . ##EQU00002##
[0171] Any one of the above parameters, namely .kappa., .epsilon.,
.epsilon.'.sub.r, .epsilon.''.sub.r, .sigma., and/or
.epsilon.''.sub.rd, may be referred to herein as a dielectric
parameter. The term dielectric parameter encompasses also
parameters that are directly derivable from the above-mentioned
parameters, for example, loss tangent, expressed as
tan .times. .sigma. = .epsilon. r '' .epsilon. r ' ,
##EQU00003##
complex refractive index, expressed as n= {square root over
(.epsilon..sub.r)}, and impedance, expressed as
Z .function. ( .omega. ) = i .times. .omega. .sigma. + i .times.
.omega. .times. .epsilon. r .times. ( with .times. i = - 1 ) .
##EQU00004##
[0172] Herein, a value of a dielectric parameter of a material may
be referred to as a dielectric property of the material. For
example, having a relative permittivity of about 100,000 is a
dielectric property of a 0.01 Molar KCl solution in water at a
frequency of 1 kHz, at about room temperature (20.degree., for
example; it should be noted that some dielectric properties exhibit
temperature dependence). Optionally, a dielectric property more
specifically comprises a measured value of a dielectric parameter.
Measured values of dielectric parameters are optionally provided
relative to characteristics (such as bias and/or jitter, for
example) of a particular measurement circuit or system. Values
provided by measurements should be understood to comprise
dielectric properties, even if influenced by one or more sources of
experimental error.
[0173] Measurement(s) during a cardiac treatment are potentially
affected by the heartbeat (cardiac cycle), the respiration
(respiratory cycle) and the rhythm(s) of the cardiac and/or
respiratory cycles as well as other factors. Typically, data
collected is assigned to an associated phase (e.g., a phase within
the respiratory cycle or cardiac cycle) and/or condition of the
heart (e.g. state of adrenergic stimulation, state post fast
pacing, state post infusion of volume of saline, etc.) for
correctly mapping the heart.
[0174] For example, conventional technologies use cardiac gating to
collect data acquired from a roving catheter only at a specific
point in the cardiac cycle (e.g. during an R wave of the body
surface ECG--denoting the ventricular activation). The gating
creates a data set, R-wave gated in this example, which is a
sub-set of a complete data set that was potentially possible to
acquire in the procedure. However, this gating algorithm has a
limitation of potentially not gathering or not using of most of the
data acquired (the non R-wave gate(s)). Similarly, a method that
gates respiration by using a trigger that identifies a repetitive
discrete indication of the respiratory cycle (beginning of
inspiration for example), will improve usability of data acquired
but will reduce even further the size of a useable data set for
purpose of accurate construction of a model. Conventional
technologies for data gating may potentially reduce the size of the
useable data even more when they require simultaneous gating of
more than one periodic cycle (e.g. cardiac and respiration).
[0175] To overcome such a limitation, conventional technologies
sometimes widen the time window during which data is acquired and
is used for construction of a model of a heart structure. By
widening the time window, these technologies potentially reduce
significantly the quality (sharpness, clarity, etc.) of a composed
image.
[0176] Furthermore, conventional technologies may face a problem
when attempting to compose an image or construct a model of a
chamber when the chamber is operating at rhythms additional to the
respiratory and cardiac rhythms that are to be accounted for when
composing the image. Such rhythms include, for example, rhythms
during various cardiac states such as during an arrhythmia, atrial
fibrillation, ventricular fibrillation (VF); and during modes of
cardiac activation (e.g. pacing), drugs, etc.
[0177] An aspect of some embodiments of the invention relates to
transforming medical data captured under different circumstances to
a common framework, registered to a common coordinate system.
[0178] In the present specification and claims, the term model is
used to describe a set of structural features and spatial
relationships between them. For example, in some embodiments, a
structural feature that appears in a source image or model at
certain spatial relationships to other features, is transformed to
appear in a target image in the same spatial relationship to the
other features, as the feature appeared in the source image.
[0179] For example, if a feature appears in the source image at
halfway between the lower and upper left pulmonary vein ostia, or
approximately there, after a transformation into a common framework
in a target image, the feature will appear in the target image half
way between the lower and upper left pulmonary vein ostia or
approximately there. This will still be the case even if the
distance between the lower and upper left pulmonary vein ostia is
substantially different between the source image and the target
image.
[0180] In some embodiments, such a transformation is achieved by
registering the source image to the target image. In some
embodiments the registration includes finding an optimal
transformation between the features that appear in the source image
and the features that appear in the target image. Optionally, the
transformation is "optimal" in the sense that the transformation
minimizes a predetermined cost function, which penalizes for
unwanted characteristics of the transformation. In some
embodiments, the transformation minimizes a cost function having a
term that penalizes more heavily the larger an unwanted
characteristic of the transformation becomes.
[0181] One such unwanted characteristic may be a large misfit.
Misfit may be defined as a parameter indicative of the difference
between features on the target image and features on the
transformed source image, and may be quantitatively measured by a
mean square of differences between locations of transformed
features and locations of the same features in the target image.
That is, if after transformation the features in the two images
perfectly overlap, the misfit is minimal, and the misfit increases
as differences between features in the target image and the
transformed source image increase. Thus, an optimal transformation
may be found by searching for a transformation that minimizes a
cost function that panelizes for misfit. In some embodiments, the
misfit penalty may be the only penalty term in the cost function.
Alternatively, the cost function may include a plurality of penalty
terms, in which case, the misfit is usually one of the penalty
terms.
[0182] Another unwanted characteristic of a transformation may be
spatial incoherence. Spatially incoherent transformation transforms
nearby features in the source image to far apart features in the
target image. Spatially coherent transformation, on the other hand,
transforms nearby features in the source image to nearby features
in the target image, and features that are far apart from each
other in the source image--to features far apart from each other on
the target image. Optionally, the distances are measured using
units of the above-mentioned coordinate system, for instance, in
units of a distance between two features, like between the two
ostia in the above example.
[0183] Thus, in some exemplary embodiments, an optimal
transformation may be found by searching for a transformation that
minimizes a cost function that penalizes for spatial
incoherence.
[0184] In some embodiments, a probe that measures a structure of
the body organ moves in respect to the body organ. For example, the
probe may be a catheter that moves inside a blood vessel to be
modeled. In some embodiments, the probe may be stationary in the
heart, and the heart may move in respect to the probe, expanding
and contracting in accordance with the cardiac cycle. In some
embodiments, the probe may move inside a beating heart. In all the
above examples, the movement between the organ and the probe may
cause the probe to measure different portions of the body organ at
different times. Often, the body organ portions measured at the
different times partially overlap with each other. The data
received from the probe may be binned according to the time at
which the data was gathered, for example, in bins of 0.1 sec, 0.5
sec, 1 sec, 5 seconds, 10 seconds, or any other time window. In
some embodiments, sequential time windows may overlap, for example,
the first bin may include data collected through seconds 0 to 10,
the second bin may include data collected through seconds 3 to 13,
etc. In some embodiments, every two sequential time windows
partially overlap with each other.
[0185] In some embodiments, each bin of data may be used to form an
image, by any method known as such in the field, for example, in
the manner described in International Publication of PCT
Application WO 2018/130974, the content of which is incorporated by
reference herein in its entirety. The images may be registered to
one another, as described below.
[0186] The images are registered to one another, so that at an end
of a registration process, some or all the features that appear in
the source images, including features that appear only in one or
some of the source images, are included in a target image, and
appear in the target image retaining their spatial relationships to
other features in the modeled body organ portion. In some
embodiments some measure of the differences between spatial
relationships in the source image and the target image is
minimized. The measure may be, for example, a mean square of the
differences.
[0187] In some embodiments, a sequence of the source images is
transformed and combined into a single combined target image by a
sequence of transformations. Each transformation in the sequence of
transformations may transform an associated image in the sequence
of the images. In some embodiments, the sequence of transformations
is required to be temporally coherent. In this context, temporal
coherency of a sequence of transformations is achieved if each
transformation continues a trend of the previous transformation.
For example, a point that is displaced in a certain direction by
one transformation is displaced in a similar direction by the next
transformation in the sequence. One non-limiting exemplary method
to ensure that a set of transformations is temporally coherent is
by verifying that a transformation obtained by subtracting any one
of the transformations in the sequence from the one before (or
after) it in the sequence, is spatially coherent.
[0188] Thus, in some embodiments, a sequence of transformations is
defined by searching for a sequence of transformations which
minimizes a cost function that penalizes for temporal incoherence.
Such a penalty may be in addition to a penalty on spatial
incoherence of each of the transformations in the sequence.
[0189] In some embodiments, the movement of the body part in
respect to the probe is periodic. For example, the cardiac cycle
and the respiratory cycle may each introduce a periodic movement
between a probe and a body organ, e.g., the heart. As in each
period the heart may go through the same stages (at least when the
cardiac cycle is normal), it is reasonable to expect that images of
the same body organ portion, taken at the same phase of the cycle,
should be substantially the same. Therefore, in some embodiments,
the source images and the transformations are ordered in accordance
with their position on the cardiac cycle (also referred to as
cardiac phase) and/or their position on the respiratory cycle (also
referred to as respiratory phase). The ordering potentially enables
combining source images taken during different heart beats into a
combined target image, potentially maintaining the spatial
relationships between the features in the different images.
[0190] In some cases, the movement of the body part changes rhythm,
for example, a heart can change its beating rate, from beating at a
first sinusoidal rate to beating at a second sinusoidal rate, or to
atrial fibrillation. In some embodiments, each such mode of
movement (e.g., the first rate, the second rate, and the atrial
fibrillation), is treated separately. That is, a plurality of
images is taken from each movement mode separately, and a separate
combined image is generated for each mode. Optionally, the combined
images may be further combined with each other to a single combined
image, e.g., by conventional registration methods.
[0191] In some embodiments, a sequence of single, combined, images
is formed and presented as a movie, with each image in the single
being a frame in the movie. In some such embodiments, each frame in
the movie is a combined image obtained by transforming and
combining the very same set of images. Preferably, the images are
constructed from data bins of measurements, each measured within a
specific time window, with a substantial overlap between time
windows. The larger is the overlap, the smoother a movement seen in
the movie. For example, each of the time windows may have 90%
overlap with a preceding time window in the sequence and with a
subsequent time window in the sequence. For example, the time
window of the first bin may be between 0 and 100 msec; the next:
between 10 and 110 msec; the next between 20 and 120 msec, etc.
Images formed from each data bin, that is, each time window, are
optionally registered to one of the images, referred to herein as a
master-image, by a sequence of temporally coherent transformations.
For example, if image #1 is the master image, the sequence of
transformations register image #2 to image #1, image #3 to image
#1, image #4 to image #1, etc. All the transformed images are
optionally combined to a single image, referred to herein as frame
#1.
[0192] In some embodiments, the same process is repeated with image
#2 as the master-image, to form frame #2. When all the frames are
ready, they may be displayed as a movie. It was found that such a
movie describes the movement that the heart underwent when the data
was collected. Each frame in movie prepared this way may be based
on the same information, except for having a different image as the
master-image.
[0193] In some embodiments, a bin of data is treated as if it forms
an image. For example, each data point in the bin representing
values of measurements in a measurement space may be linearly
transformed to form an image. For example, in some embodiments,
voltage values of one, two, three electromagnetic fields, or even
more, are optionally measured, simultaneously. In some embodiments
each electromagnetic field being characterized by a different
frequency. A data point in the bin may be a set of three voltage
values, simultaneously measured at the three frequencies. An image
of the data in the data bin may include points shown on a Cartesian
coordinate system. In some embodiments the length of the axes may
be, for example 1 cm (or some other length) for each measured mV.
In such embodiments, after the images are registered and combined
as described above, the obtained combined image may be used to form
an image in real space (rather than in measurement space), by any
way known as such in the field, for example, in the method
described in the above-mentioned PCT Application WO
2018/130974.
[0194] In some embodiments, the above-mentioned image may be a
point cloud. In some embodiments, point clouds (in measurement
space or in real space) from different data bins are transformed
and combined to obtain a single combined point cloud, and the
combined point cloud is then optionally used to reconstruct an
image in which the points are connected, e.g., by a smooth surface.
The reconstruction may be by any method known as such in the field
for constructing images from point clouds, for example, by using a
ball pivoting algorithm.
[0195] In some embodiments, an image of a received sequence of
images includes an indication of where a certain predefined region
is present in the image. For example, in an embodiment where the
imaged body part is the right atrium, data points corresponding to
the fossa ovalis may be marked on each of the images of the
sequence. In such embodiments, a search may be for a sequence of
transformations that transform marked regions (i.e., regions
defined by marked data points) in source images, to marked regions
in a target image. A requirement for transforming marked regions to
marked regions may expedite the search for the transformations.
Similarly, in some embodiments, a physician keeps the probe steady
at one point for one or more sequential periods of movement of the
body part (e.g., the probe may be pushed against an arbitrary point
on the heart wall for several heart beats). Readings of the same
values during several periods may be marked, and such marking may
be used for defining a sequence of transformations that transform
the marked regions to marked regions, expediting the search for an
adequate sequence of transformations.
[0196] In some embodiments the common framework is a common
geometric, spatial framework, where data points include geometric
locations using a common spatial coordinate system. For example, in
some embodiments when locations of electric measurements such as
voltage measurements are known, the locations may use a common
spatial coordinate system, for example measured in units of
distance relative to some origin location in space.
[0197] In some embodiments the common coordinate system includes a
common temporal coordinate, where data points include temporal
location described in the common temporal coordinate. By way of a
non-limiting example, electric values measured during two different
cardiac cycles may be combined into one data set based on their
temporal coordinates, such as a time along a cardiac contraction
cycle or phase of the cardiac contraction cycle. By way of a
non-limiting example, electric values measured during movement of a
probe along an artery may be combined into one data set based on
their temporal coordinates, that is, time measured since a specific
time origin. In some embodiments the data from the different
circumstances is used to produce an image, based on having the
common geometric and/or temporal coordinate systems. Different
circumstances optionally include different cardiac pulse phases,
different cardiac pulse pathologies, different breathing phases,
and different breathing rates. Many times using different
coordinate systems affects measured values.
[0198] An example scenario of medical data captured under different
circumstances is described below. The scenario is not intended to
limit the scope of the invention, but to explain the issue of
capturing medical data under different circumstances. Persons
skilled in the art are able to understand the application of the
example under additional scenarios.
[0199] When collecting medical data, by way of a non-limiting
example in a living, breathing patient, the patient or portions of
the patient for which the medical data is collected, may be moving.
In many cases the medical data acquires different values when the
patient is moving; breathing; his heart is beating, and so on.
[0200] Collecting medical data may include, by way of a
non-limiting example, measuring one or more electrical readings,
for example: (optionally simultaneous) electric voltage readings or
electric field readings in an intra-body probe or catheter. In some
embodiments, the probe includes several electrodes, and provides
several simultaneous measurements. As used herein, "electrical
readings" are interchangeable with "electric measurements" and
represent direct electrical measurements such as voltage and
current, as well as values calculated based on the direct
electrical measurements such as impedance (electric) and other
electric and/or dielectric parameters. Collecting medical data may
also include non-electrical readings, by way of some non-limiting
examples magnetic readings, location data, pH data.
[0201] As used herein, electric measurements may include any
measured electric parameters and/or dielectric parameters, either
directly measured or calculated from the measured parameters, for
example: voltage, current, conductivity, resistivity, reactance,
admittance, etc. Electric measurements may be obtained by one or
more electrodes, which may be carried, for example, on an
intra-body probe; for example an ablation catheter; a split tip
catheter; a balloon catheter; a coronary sinus catheter, a lasso
catheter, a multi-prong catheter; a basket catheter Optionally,
each such probe may carry one or more, for example 2, 3, 4, 10 or
20 electrodes. In some embodiments, the electrodes may include
electrodes outside the body, for example, ECG body surface leads;
body-surface patch electrodes, etc.
[0202] Electric and dielectric measurements may be obtained by one
or more electrodes provided on an ablating catheter. Electric
measurements may be obtained by one or more sensors provided on a
dedicated intra-body probe, e.g., used solely for such electric
measurements. Electric measurements may be obtained at a single
frequency or at a plurality of frequencies. In some embodiments,
electric measurements include measurement at various frequencies,
e.g., from about 10 kHz to about 1 MHz. In some embodiments,
electric measurements may include complex values. In some
embodiments, electric measurements may include impedance
measurements including measurements of impedance between different
electrodes on the ablation catheter (e.g., between a tip electrode
on a probe of the ablation catheter and another electrode on the
same catheter), between one or more electrodes on the ablation
catheter and one or more electrodes on another catheter, and/or
between one of more of the ablation electrodes and one or more body
surface electrodes.
[0203] Collecting the medical data may include, by way of a
non-limiting example, measuring one or more simultaneous electric
voltage readings or electric field readings from an external
electrode placed on a patient's body. In some embodiments, several
electrodes are placed on the patient's body, and optionally provide
several simultaneous measurements.
[0204] By way of a non-limiting example, in cardiac imaging, a
heart changes shape over a heartbeat. In fact, many patients'
hearts may change shape differently in case of different types of
heartbeat. A heartbeat which exhibits atrial fibrillation changes a
shape of a heart differently, and may develop differently over
time, than a heartbeat which does not exhibit atrial
fibrillation.
[0205] In some methods of collecting medical data, one uses gating
to compensate for heart beat and respiration. In such methods,
medical data is captured, or used, only when the medical data is
within a specific gate of time during which the data does not
change much. Medical data outside the specific gate of time is
either not captured, or, if captured, not used together with data
from another timing gate.
[0206] However, not using medical data from different gates of time
means using less data. By way of a non-limiting example, using less
data may cause a loss in resolution of a medical image, and/or a
loss in accuracy, and/or not imaging a portion of a desired image,
and/or taking more time to produce a desired image.
[0207] By way of a non-limiting example, when using intra-body
electrical readings to construct an anatomical structure of a
heart, one or both of an intra-body electric probe and the heart
are moving, and data captured may pertain to different portions of
a heart at different times. Constructing anatomical structure of a
heart is described, for example, in above-mentioned PCT Application
WO 2018/130974.
[0208] By way of a non-limiting example a scenario as described in
the above paragraph may use 6-8 time windows to bin data for
movement over a heartbeat cycle, and 4-6 gates to bin data for
movement over a breathing cycle. Using medical data from just one
heartbeat data bin or breathing data bin means leaving some or even
most of the collected data unused.
[0209] In some embodiments data is not necessarily binned. In some
such embodiments, each data point has associated with it a phase
indicator, which may include values indicative of time the data
point was captured from beginning of heartbeat cycle and/or phase
of heartbeat cycle at which the data point was captured, and/or
time from beginning of breathing cycle to the capture of the data
point and/or phase of breathing cycle at which the data point was
captured. The value is optionally used to transform data points to
share a common temporal coordinate system, that is, to refer to a
common time of beginning of the heartbeat cycle. In some
embodiments the value is optionally used to group data points with
similar values to be transformed together without data points being
divided or stored into actual data bins.
[0210] If no data gating or binning is used, images (e.g., heart
image or portions thereof) generated using data from different
cardiac contraction phases and/or different respiratory phases may
cause blurring of the images.
[0211] In cardiac electrophysiology (EP) medical procedures,
acquisition of electrical readings and/or medical data can extend
over several seconds, several minutes, and even several hours. In
such cases a cardiac image may be updated, for example during the
medical procedure; such that new data may be collected and
calculated `offline` to create a new or updated image; e.g. to
compensate for changes during the procedure. Furthermore, patients
may be suffering from cardiac arrhythmias; and during the procedure
the patients' hearts may switch between different rhythms, many of
the rhythms presenting a different shape for different data bins
when compared to a shape of a heart in normal rhythm. Therefore,
heart maps or images produced during EP procedures may be
misleading as they may contain information acquired during one
heart rhythm which has little resemblance to another rhythm during
which an operator currently navigates in a heart.
[0212] Some challenges that are faced when imaging a heart with a
roving catheter are:
[0213] a. The heart beats--the heart shape and size changes its
geometry during the cardiac cycle and the heart electrical
properties;
[0214] b. The patient breathes--which changes the geometry of the
heart and electrical properties of the chest during the breathing
cycle;
[0215] c. The heart can change its activation and contraction
(activation pattern--causing the contraction pattern).
[0216] An aspect of some embodiments of the invention relates to
transforming data (e.g., electrical readings) obtained from an
intra-body probe to use a common coordinate system in order to use
the data to image anatomical structure. Example scenarios of the
transforming are described herein. The scenarios are not intended
to limit an extent of the concept of transforming of medical data
captured under different circumstances to use a common coordinate
system, but to explain. Persons skilled in the art are able to
understand the transformation for additional scenarios.
[0217] According to some embodiments of this invention, medical
data from more than one bin is used to create an image.
[0218] In some embodiments, medical data from one data bin is
transformed, and the transformed data is combined with medical data
of a second data bin. The combined data is optionally used to
create an image. The image may be a static image or a dynamic
image.
[0219] In some embodiments, the image is optionally dynamically
updated during a medical procedure, producing a dynamic,
potentially changing and/or updating image.
[0220] In some embodiments, new medical data is optionally
collected and calculated to produce a new static image.
[0221] In some embodiments, medical data is optionally collected
for many or even all data bins and is optionally transformed to
maintain a correspondence between data from different data bins,
such transformation of data from one data bin to another is termed
herein "gate projection".
[0222] An aspect of some embodiments of the invention relates to
means and methods for synthesis of an image originating from data
from multiple data bins in a phase and/or state corrected
manner.
[0223] In some embodiments, the medical data of each bin
potentially corresponds to data suitable for synthesizing multiple,
potentially co-located images. In some embodiments the multiple
images are separate discrete images.
[0224] An aspect of the invention relates to a method to use all or
a majority of data (e.g., medical data) acquired while imaging or
mapping the heart with a roving catheter. The roving catheter data
acquisition potentially creates a sparse data set which means that
in part of the locations that the catheter visits the catheter
collects data that was captured at a different phase or mode of a
breathing cycle, or a different mode of a cardiac cycle.
[0225] In some embodiments of the invention, a method is used to
project, based on producing a transformation, data from several
bins into one existing bin or one new bin which serves as a common
reference bin, and use more of the data that was acquired, and in
some embodiments all of the data that was acquired.
[0226] It is noted that medical data may have various dimensions,
for example time, location, cardiac cycle phase, pressure phase,
temperature, and a phase in the breathing cycle.
[0227] An aspect of some embodiments of the invention relates to
producing a transformation of data that transforms data from one
data bin to another data bin within a same dimension, and
transforms data from one data bin to another between dimensions. In
some embodiments, the transformation is a rigid transformation of
some or all of the data from one data bin to another data bin.
[0228] By way of a non-limiting example, a location of a catheter
is known based on at least two points during a cardiac cycle, a
transformation is optionally produced that accepts a phase of the
cardiac cycle and provides a location of the roving catheter at
that phase.
[0229] In some embodiments, the transformation operates on a
multi-dimensional sparse matrix of acquired data.
[0230] In some embodiments, the transformation generates an optimal
transformation within each of the dimensions.
[0231] In some embodiments, the transformation generates a
transformation which in some embodiments, the transformation
generates an optimal transformation within each of the dimensions.
In some embodiments an image is produced by using transformed data.
In some embodiments, the transformation generates an optimal
transformation within each of the dimensions.
[0232] In some embodiments, an optimal transformation is optionally
generated within all or part of the dimensions simultaneously.
[0233] In some embodiments, the transformation is applied to the
sparse matrix and optionally fills in missing data by
interpolation.
[0234] In some embodiments, the data populates a multi-dimensional
matrix. For example, each type of measurement is optionally a
dimension, and/or different bins may optionally be defined as
dimensions of a measurement. In some embodiments, when projecting
from a multidimensional matrix to a specific point in the cardiac
cycle a reduction of at least one dimension in dimensionality of
the data is achieved, by eliminating the cardiac cycle
dimension.
[0235] In some embodiments, the projection is used to reduce one or
more dimensions of the multi dimension data.
[0236] In some embodiments, the projection is used to transform
data to share a common geometric coordinate system, optionally
transforming geometric coordinates associated with data points of a
data bin to have a same geometric coordinate system as data points
of another data bin.
[0237] In some embodiments, the projection is used to transform
data to share a common temporal coordinate system, optionally
transforming time measurements associated with data points of a
data bin to have a same temporal coordinate system as data points
of another data bin. By way of a non-limiting example, data points
captured during different heartbeats may optionally be transformed
to be associated with duration since a beginning of a heartbeat
rather than clock time. By way of another non-limiting example,
data points captured during different breathing cycles may
optionally be transformed to be associated with duration since a
beginning of a breathing cycle rather than clock time.
[0238] The term "sparse data set" in all its grammatical forms is
used throughout the present specification and claims to mean a data
set in a data bin in which the ratio of filled to empty spaces is
low. By way of a non-limiting example, for a given spatial
resolution, the data set is sparse when entries for some locations
in the second data bin are missing from the first data bin.
[0239] In some embodiments, temporal coherence facilitates a search
for correspondence between extremely sparse (and potentially
disjoint) data sets.
[0240] For purposes of better understanding some embodiments of the
present invention, reference is first made to FIG. 1, which is a
simplified line drawing illustration of images produced of a
portion of a heart at two time points according to a prior art
method of imaging.
[0241] FIG. 1 illustrates a problem with imaging the heart when the
heart is moving due to breathing, changing size and shape due to
the heart beating, and optionally using an imaging modality which
does not necessarily capture an entire image of the heart at one
point in time.
[0242] FIG. 1 shows a first line drawing illustration of an example
first image 101 of a portion of a heart, for example an atrium, at
a first point in time, and a second line drawing illustration of an
example second image 102 of the very same heart atrium at a second
point in time.
[0243] The first image 101 is shown larger than the second image
102, to illustrate that the atrium may have contracted at the
second point in time. The first image 101 is shown shifted in space
relative to the second image 102, to illustrate that the atrium may
have moved within the patient's chest, possibly due to breathing,
between the first point in time and the second point in time.
[0244] By way of a non-limiting example, the first image 101 is
shown displaying a section 101A which the second image 102 does not
display, and not displaying a section 101B which the second image
102 does display. The second image 102 is shown displaying a
section 102A which the first image 101 does not display, and not
displaying a section 102B which the first image 101 does
display.
[0245] FIG. 1 shows images of the atrium during points in time T0
and T1.
[0246] Data for producing the image 101 may have been captured when
an intra-body probe was in a position to capture data for the
section 101A, and not capture data for the section 101B, and
similarly for data for producing the image 102.
[0247] In prior art imaging, the difference in dimensions such as
shape, size, physical location in space between the first image 101
and the second image 102 would cause the data for producing the
second image 102 to be unused, so as not to attempt to produce a
combined image which is smeared or distorted, resulting in a
smeared image. Combining data from time T1 to data from time T0
would potentially distort and/or blur the combined image.
[0248] Data captured under different conditions, for example at
different times, is sometimes kept separate, and the separation is
sometimes termed "gating" or "binning".
[0249] Before explaining at least one embodiment of the invention
in detail, it is to be understood that the invention is not
necessarily limited in its application to the details of
construction and the arrangement of the components and/or methods
set forth in the following description and/or illustrated in the
drawings and/or the Examples. The invention is capable of other
embodiments or of being practiced or carried out in various
ways.
[0250] Before explaining at least one embodiment of the invention
in detail, it is to be understood that the invention is not
necessarily limited in its application to the details set forth in
the following description or exemplified by the Examples. The
invention is capable of other embodiments or of being practiced or
carried out in various ways.
[0251] In some embodiments of the invention, data for producing the
second image 102 is optionally transformed by registering to the
first image 101. In some embodiments, the transform is by a
transformation based on portions of the anatomical features common
to both the first image 101 and the second image 102.
[0252] In some embodiments, the transformation is based on all the
portions of both images. In some such embodiments the
transformation is performed without first identifying common
portions in both images.
[0253] In some embodiments the transformation is optionally a rigid
transformation of some or all of the data points associated with
anatomical features in the second image 102 which are common to the
first and second images.
[0254] Optionally, the transformation, rigid or not, is determined
so that a good fit is achieved of an image or mapping of the data
points in the second image 102 which are common to the first image
101. Some non-limiting examples of what is optionally considered
good fit include: small misfit between features in the image
obtained by transforming image 102 and in image 101; spatial
coherence of the transformation; a smoothness of a shape of an
object imaged by the transformed data points; a correct or
approximately correct volume of an object imaged by the transformed
data points; a number and/or size and/or relative location of fixed
anatomical structures (e.g. veins, arteries, valves) in an image
which was produced by the transformed data points; and fulfilling
expectations of an expected change to an anatomical structure due
to an altered rate or rhythm--for example, a size of a chamber is
typically smaller at higher cardiac rates, the size of the chamber
is typically larger during fibrillation.
[0255] In some embodiments, the transformation is optionally a
rigid transformation of some or all of the data points associated
with anatomical features in the second image 102 which are common
to the first image 101 and the second image 102.
[0256] In some embodiments a transformation is optionally an affine
transformation that minimizes displacement between a transformed
shape and a target shape and/or transformed points and a target
shape.
[0257] Reference is now made to FIG. 2, which is a simplified line
drawing illustration of transforming data points from one data bin
to another data bin, and using data points from both data bins to
produce an image, according to some embodiments of the
invention.
[0258] FIG. 2 shows a first line drawing illustration of the
example first image 101 as described above with reference to FIG.
1, and a second line drawing illustration of an example second
image 102C. The second image 102C is optionally produced based on
the second image 102 described above with reference to FIG. 1,
which has been transformed by a resizing transformation and/or a
rotation transformation and/or a shifting transformation, so that
at least a portion 102D is transformed by a transformation T to
correspond to a portion 101D of the first image 101.
[0259] FIG. 2 shows a third line drawing illustration 200 produced
202 by combining 201 the example first image 101 and the second
image 102C.
[0260] A transformation which transforms data points from one data
bin, for example that used to produce the second image 102 of FIG.
1, to a transformed set of data points, for example that used to
produce the second image 102C of FIG. 2, is termed herein "gate
projection" and "bin projection".
[0261] Collecting Data
[0262] In some embodiments medical data is received. Some data is
physical data, such as time and location/space measurements. Some
data is processed data, such as a decision whether a data point
belongs to an ECG measurement of a chaotic heartbeat or a
non-chaotic heartbeat.
[0263] In some embodiments receiving the data is practically
continuous, such as time and location/space measurements. In such
cases actual measured values may be recorded even if the values are
eventually collected into bins, such as time-window bins.
[0264] Binning Data
[0265] In some embodiments medical data is arranged in time domain
data bins, that is, data measured at different times is arranged
according to the time the data was collected, optionally in time
windows. In some embodiments, the data arranged in time domain data
bins corresponds to a sequence of images, or movie frames.
[0266] In some embodiments Electro-Cardio-Gram (ECG) measurements
are gated or binned based on belonging to an identified phase in
the cardiac rhythm--e.g. binned according to one or more of: P
segment, PR interval, PR segment, Q, R, S, QRS complex, ST segment,
QT interval, and T.
[0267] In some embodiments, measurements indicative of the
structure of the body part to be imaged are gated or binned
according to an identified phase in the cardiac rhythm, during
which the measurement were taken. Optionally, measurements taken
during different phases are used to produce different single
images. The single image of a cardiac phase may be generated from
images based on measurements made during a plurality of time
windows, all within the same phase, even if not of the same cycle.
For example, data from the P segment (or any other segment) of one
heartbeat may be binned into the same bin, and used to generate a
same source image, as the P segment of another heartbeat (e.g., a
sequential heartbeat). In some embodiments, the source images are
ordered in the sequence according to their phase in a cycle of the
periodic change that the imaged body part undergoes, for example,
according to their phase in heartbeat.
[0268] In some embodiments, after a single image is generated for
each of two or more phases, the single images are registered to
each other and combined to provide a combined image showing details
observed during different phases.
[0269] In some embodiments ECG measurements are optionally binned
to one or more data bins belonging to a normal rhythm (e.g.,
sinusoidal) and to one or more data bins belonging to an abnormal
rhythm (e.g., atrial fibrillation). Similarly to the above, data
measured during a normal rhythm may be binned separately than data
measured during an abnormal rhythm, and a different single image
may be generated for each rhythm type.
[0270] In some embodiments ECG measurements are optionally binned
to one or more data bins belonging to a cardiac rhythm types
including: a chaotic beat; an atrial fibrillation beat; a first
type of dominant beat; a second type of dominant beat; and a third
type of dominant beat.
[0271] In some embodiments, dominance of a beat is based on a ratio
of beats that belong to a specific rhythm or form, where form is a
type of beat, such as sinus beat, atrial premature beat,
ventricular premature beat, post premature beat, bigeminy, blocked
beat, etc. Measurements made during different types of dominant
beats may be binned to different data bins.
[0272] In some embodiments ECG measurements are optionally
processed to identify R-wave in the ECG measurements. The ECG
measurements are optionally evaluated from time points starting at
the R-wave, whether a heartbeat belongs to a chaotic heart rhythm
or a normal heart rhythm. In some embodiments if a heartbeat
belongs to a chaotic heart rhythm, such as, by way of some
non-limiting examples, an atrial fibrillation (AF) rhythm and some
premature beats, measurements belonging to the chaotic heartbeat
are optionally binned in a "chaotic" data bin.
[0273] In some embodiments if a heartbeat does not belong to a
chaotic heart rhythm, measurements belonging to the non-AF
heartbeat are optionally additionally processed, and additional
segmentation of the beats in the non-AF rhythm is optionally
performed. In some embodiments a covariance-based classifier is
optionally used to select three classes of non-AF heart beats. A
first type of dominant beats are optionally binned to a first bin,
for example termed bin A, and a second type of dominant beats to a
second bin, for example termed bin B, and other non-AF beats are
optionally binned to a third bin, for example termed bin C.
[0274] In some embodiments, measurements are binned based on their
phase within a breathing cycle, where each measurement is binned
according to a breathing phase in which the measurement was taken.
In some embodiments phases in a breathing cycle may be identified
based on body-surface impedance measurements.
[0275] In some embodiments body-surface impedance measurements are
gated or binned based on belonging to an identified phase in a
breathing rhythm.
[0276] In some embodiments a signal from body-surface impedance is
optionally processed to identify phases in a breathing cycle.
[0277] Alternatively or additionally, measurements may be binned
according to the breathing cycle during which they were measured,
without relation to breathing phase. For example, a cycle may be
identified and binned to a number of bins of equal duration (e.g.,
of 0.1 second, 0.5 second, 0.8 second, 1 second, 3 seconds, 6
seconds, 10 seconds, 20 seconds, or intermediate number of
seconds).
[0278] In some embodiments peak detection in a signal of a sensor
measuring breathing is optionally performed to identify a start of
a breathing cycle (BB), defined as time between consecutive
breaths. An exemplary method for detecting breathing peaks may be
found in the article "A robust detection algorithm to identify
breathing peaks in respiration signals from spontaneously breathing
subjects", published in 2015 Computing in Cardiology Conference,
DOI: 10.1109/CIC.2015.7408645, the disclosure of which is
incorporated herein by reference.
[0279] In some embodiments a covariance classifier is used to
segment BB signals into a first data bin, e.g. breathing bin A, for
base respirations, a second data bin, e.g. bin B, for short
breathing cycles, and a third data bin, e.g. bin C, for long, for
example sigh-type, breathing cycles.
[0280] Reference is now made to FIG. 3A, which is a simplified
block diagram illustration of a system for measuring medical data,
classifying and/or binning the medical data, and transforming the
medical data to use a common coordinate system according to some
embodiments of the invention.
[0281] FIG. 3A shows components in a system 311 constructed
according to an exemplary embodiment of the invention.
[0282] The system optionally includes one or more measurement
component(s) 312 for collecting measurements 310 from a patient's
body. Measurement components 312 may include, for example, body
surface electrodes and/or intra-body electrodes. The measurements
optionally include patient-related signals with information
regarding one or more periodic signals, for example body surface
ECG or intra-cardiac electrograms, chest wall dimension, and
optional physical measurements such as time, location in space
(e.g., of the intra-body electrodes), temperature (e.g., in
vicinity to an ablation site), pressure (e.g., of a catheter
against a tissue or blood pressure measured by a sensor on a
catheter) and so on.
[0283] In some embodiments, measurement component(s) 312 may not be
part of system 311, and the measurements may be otherwise provided
to system 311, e.g. through one or more interfaces connecting
external measurement components to processing component 316 and/or
projecting component 320.
[0284] An output 314 of the measurement component(s) 312 is
optionally a signal and/or digital data which is affected by a
patient's physiology, for example a body-surface ECG, data of
occurrence times of R waves, data of the occurrence times of
initiation of respiration, body surface impedance (optionally
continuous), instantaneous heart rate, amplitude of respiration,
CO.sub.2 content or concentration in the breath, acoustic signal of
the chest, etc.
[0285] The output 314 optionally serves as input to a processing
component 316 which may be, for example, a computer or a central
processing unit. Thus, output 314 may also be referred to as input
314.
[0286] In some embodiments, processing component 316 receives
output 314 of the measurement component(s) 312 in units of voltage,
and calculates values of resistivity, reactance, or other
dielectric properties based on the voltage. The values may
optionally include a discrete time series of values measured during
one or more rhythms, and/or analog values in a continuous measure
of the rhythm, for example a blood pressure wave, nasal airflow,
etc.
[0287] The processing component 316 optionally calculates one or
more classification values associated with one or more rhythms in
patient's physiology and/or associated with different stages in the
rhythms. Such associated classification values may be referred to
herein as descriptors.
[0288] In some embodiments, the processing component 316 receives
output 314 of the measurement component(s) 312, and calculates
whether the electric signal corresponds to a sinus cardiac rhythm
or to an arrhythmia based on the voltage values, and/or a phase of
cardiac rhythm to the received output. In some embodiments,
processing component 316 may calculate its output based on a time
that elapsed from a beginning of the cardiac rhythm. Optionally,
the beginning of the cardiac rhythm is also detected by the
processing component based on data input 314.
[0289] In some embodiments, the processing component 316 optionally
processes separately data collected in different states. The
different states may include, for example, normal heart beating or
arrhythmia, such as atrial fibrillation. Different states may also
be different types of breathing, such as calm breathing, strenuous
breathing, shallow breathing, deep breathing, etc. For this end, in
some embodiments, the processing component 316 optionally produces
a classification of a physiological state (e.g. sinus cardiac
rhythm or arrhythmia, normal breathing or strenuous breathing,
atrial fibrillation or ventricular fibrillation, etc.) associated
with the data input 314, such that data collected in a given state
is optionally processed separately from data collected in other
states.
[0290] In some embodiments the state classification may be input
into the processing component 316 from the measurement component
312 or electronically fed directly to the processing component
316.
[0291] In some embodiments, state classification is optionally
generated in the processing component 316 to classify a continuous
signal associated with the state.
[0292] Processing component 316 outputs an output 318 in the form
of data (e.g., in case output 318 is digital) or a signal (e.g., in
case output 318 is analog). Output 318 is optionally input to a
projecting component 320. In some embodiments, the projecting
component 320 may be part of the processing component 316.
[0293] In some embodiments, projecting component 320 and/or
processing component 316 may be configured to implement methods
described in reference to FIGS. 4A, 4B, 5A, 5B, 6A-6D, 10A-10B,
11A-11C, 12 and 13.
[0294] In some embodiments, processing component 316 optionally
classifies the output 314 as belonging to a specific state, such as
output indicative of measurements performed during a specific state
of rhythmic change, such as change in heartbeat rate, type of heart
rhythm--sinus, arrhythmic, type of breathing--shallow or deep, and
so on.
[0295] In some embodiments input to the projecting component 320
may optionally also include input from one or more electrodes (not
illustrated) optionally from an intra-body probe, optionally
collecting data for building a map of a heart chamber, including,
by way of a non-limiting example, instantaneous locations,
voltages, impedances etc., as well as the output from the
processing component 316.
[0296] In some embodiments, measurement component(s) 312 may be
configured to measure electrical readings or other medical data.
Measurement component(s) 312 may include one or more electrodes
and/or one or more sensors provided, for example, on an ablating
catheter. Output 314 of the measurement component(s) 312 is
optionally a signal and/or digital data which includes electrical
readings and/or other medical data.
[0297] In some embodiments, projecting component 320 accepts as
input 318 raw data signals measured during brief overlapping time
windows, the time windows optionally having a duration shorter than
5 msec, 10 msec, 50 msec, 100 msec, 250 msec 500 msec, 1 sec, 5
sec, 10 sec 20 sec or 30 sec. The projecting component 320
optionally transforms the overlapping data sequences (fragments) so
that the overlapping time windows are transformed to coincide with
each other. In some embodiments, some or even all of the data in
the time windows of input 318 is transformed to produce data which
describes a combined time period potentially extending longer than
the separate time windows, and using a same time scale.
[0298] In some embodiments, the projecting component 320 optionally
assigns correspondences between the overlapping segments
(fragments), and optionally recovers a transformation that maps
between the overlapping segments.
[0299] Qualitatively, a requirement that a transformation maintains
spatial coherence may be understood as a requirement that the
transformation displaces points that are near each other to new
positions that are near each other, and points that are far from
each other to new positions that are far from each other. The
displacements of points that are near each other are thus along
paths of similar directions and similar lengths. The further the
points being transformed are from each other, their displacements
may become less similar. An example of a registration algorithm
designed to provide coherent transformation is the Coherent Point
Drift (CPD) method, such as described in an article titled "Point
Set Registration: Coherent Point Drift", published on 15 May 2009
on the world-wide-web, in arxiv(dot)org/abs/0905.2635, the
disclosures of which is incorporated herein by reference.
[0300] Qualitatively, a requirement that a transformation maintains
temporal coherence may be understood as a requirement that the
transformation displaces data points along a sequence of time
periods in a smooth manner.
[0301] One non-limiting exemplary method to obtain a spatially
coherent transformation is to minimize a cost function, with less
coherent transformations being assigned a higher cost. The
coherence may be estimated, for example, by decomposing the
transformation to its spatial frequency components, and associate a
high cost for high frequency components.
[0302] One non-limiting exemplary method to obtain a temporally
coherent sequence of transformations is to require spatial
coherence from a difference between each two transformations that
transform successive images. An alternative way to obtain
temporally coherent transformation(s) is described in detail in the
article "Registration of multiple temporally related point sets
using a novel variant of the coherent point drift algorithm:
application to coronary tree matching" published in Proc. of SPIE
vol. 8669, incorporated herein by reference.
[0303] The term "adjacent" in all its grammatical forms is used
throughout the present specification and claims to mean next to or
adjoining something else, abutting, bordering (on), contiguous
with, touching, having a common vertex or a common side.
[0304] In some embodiments, a variation of the CPD method is
optionally used to calculate the correspondence between different
values of the output 318 of the processing component. In some such
embodiments, when the fragments overlap over a larger duration than
the sampling rate, the method optionally connects fragments using
the overlap to force a correct correspondence between fragments
that are close to each other spatially and/or temporally. In some
embodiments, the coherence is optionally applied in the spatial
domain. In some embodiments the coherence is optionally applied in
the temporal domain. In some embodiments, the coherence is
optionally applied in both the spatial and the temporal domain.
[0305] A brief description of CPD is now provided. CPD refers to a
family of methods, which can be used to solve a correspondence
determination of sparse data matrices. Point set registration is a
component in many computer vision tasks. A goal of point set
registration is to assign correspondences between two sets of
points and to recover a transformation which maps one point set to
the other. Multiple factors, including an unknown rigid and/or
non-rigid spatial transformation, a large dimensionality of a point
set, noise and outliers, make point set registration a challenging
problem.
[0306] In some embodiments, a probabilistic method, called a
Coherent Point Drift (CPD) method, is introduced for both rigid and
non-rigid point set registration. An alignment of two point sets is
taken as a probability density estimation problem.
[0307] In some embodiments Gaussian Mixture Model (GMM) centroids
are optionally fit, representing a first point set, to data (a
second point set), by maximizing likelihood. The GMM centroids are
optionally forced to move coherently as a group to preserve
topological structure of the point sets.
[0308] In a rigid case, the coherence constraint is imposed by
re-parametrization of the GMM centroid locations with rigid
parameters, and a closed form solution of the maximization step of
the EM algorithm in arbitrary dimensions is derived.
[0309] In a non-rigid case, the coherence constraint is optionally
imposed by regularizing a displacement field and using variational
calculus to derive an optimal transformation.
[0310] In some embodiments, a best-fit transformation is optionally
used for rigid and/or non-rigid point set registration. An
alignment of two point sets is taken as a best-fit estimation
problem. In some embodiments best-fit is calculated based on
minimizing a mean-square-error between corresponding points in a
first data set projected onto a second data set. A best-fit
transformation is termed herein a method which provides minimal
mean-square-error between corresponding points in a first data set
projected onto a second data set. The mean square error may also be
referred to herein as one exemplary form of "misfit".
[0311] In some embodiments a fast algorithm is introduced that
reduces the computation method complexity.
[0312] In some embodiments time complexity of the computation
method is optionally reduced by using a small number of base
functions to represent the transformation. The number of base
functions can be smaller than the number of points being
transformed, and produce smooth transformations.
[0313] In some embodiments the projecting component 320 produces a
transformation vector. The transformation vector transforms one or
more of locations of a roving catheter, time of measurement,
relevant mapped properties such as measured electrical values or
calculated values based on the measured values, to other locations,
times of measurement and mapped properties.
[0314] In some embodiments the projecting component 320 accepts a
phase during which values were measured, and optionally uses the
transformation vector to calculate relevant mapped values.
[0315] In some embodiments the projecting component 320 provides a
location of a same part of, for example, a heart chamber, later in
a rhythmic movement. For example, one can provide input to the
projecting component 320 of a location of the left atrial ridge (or
some other site) that was acquired at a specific point in the
cardiac cycle, and/or a specific point in the respiratory cycle,
and/or during a specific heart rhythm, and the projecting component
320 uses the transformation to determine, and in some embodiments
display, or "play", where the next locations of the left atrial
ridge will be in following times. In some embodiments, the
transformation is optionally used to make projections not only for
a future location but for future relevant sensed properties such as
electric measurements and/or dielectric measurements and/or
anatomical structure shape extrapolation.
[0316] In some embodiments, the projecting component 320 produces
an interpolator, optionally based on a transformation vector. In
some embodiments the interpolator is a transformation which
minimizes misfit, for example minimizes mean-square-error of
differences between features on a target image and features on a
transformed source image.
[0317] In some embodiments, the projecting component 320 uses the
transformation vector to map data sets measured under different
conditions, that is transform data values in the data sets, to each
other; where the different conditions can be in a spatial domain,
and/or temporal domain.
[0318] In some embodiments, the projecting component 320 makes use
of consecutive, overlapping segmented data streams (e.g.,
electrical readings) acquired at a tip of a roving catheter. The
data in the data streams describes, for example, consecutive
locations of the tip of the roving catheter together with
simultaneously recorded body-surface ECG and voltages measured
inside a heart chamber, for example, in touch with a heart chamber
wall. The data streams are optionally spliced in an overlapping
manner to yield spliced sections that have a total duration of L
msec. An operator is optionally navigating the catheter inside a
heart chamber, and wishes to construct the shape of the chamber,
for example, during an "end systole". The roving catheter visits at
an "end systole" only a fraction of the time during which the
catheter is roving within the heart chamber. According to an
embodiment of the invention, the location of the roving catheter
tip is optionally recorded together with the simultaneous body
surface ECG. The recorded data stream is optionally segmented into
consecutive L msec slices, for example 5 msec slices, every N msec,
for example every 1 msec, such that consecutive slices have for
example 4 msec of overlapping data. An ensemble of catheter tip
locations at each point in the cardiac cycle, including the desired
"end systole" point, provides a sparse set of data points.
[0319] In some embodiments, data measured at consecutive times, for
example not at "end systole", are optionally mapped to yield a
series of consecutive models, each modelling the heart chamber
structure at a different, potentially close, point in time. A
Coherent Point Drift (CPD) method is optionally applied to the
consecutive partially overlapping models to register structure of
the heart chamber at one time to its structure at another time. In
some embodiments the transformation performs an extrapolation from
a data point measured at one location in space and/or instant in
time to another point close in space and/or time.
[0320] It is noted that data points captured at a specific instant
may include multiple dimensions and/or variables. Some of the
dimensions/variables may be continuous and some of the
dimensions/variables discrete.
[0321] Gate projection, transforming data point values from one
data bin to another data bin, or to a common reference bin, may
optionally reduce a dimensionality of the data, in a sense that
data which was captured at a point in time T, which may include N
dimensions, for example 3 location dimensions, one time dimension,
M voltage readings, and so on, be recorded as N-dimensional data,
but after transformation, for example if all time-window bins are
transformed into one time-window bin, the data dimensionality may
be reduced, for example, by 1. In the above-mentioned non-limiting
example the time dimension is eliminated from the data, as all data
is transferred to a same time-window bin.
[0322] Reference is now made to FIG. 3B, which is a simplified
block diagram illustration of a system for measuring medical data
in several frameworks and transforming the medical data to use a
common framework according to some embodiments of the
invention.
[0323] FIG. 3B shows components in a system 391 constructed
according to an exemplary embodiment of the invention.
[0324] FIG. 3B shows a system which accepts input of measurements
390 and does not include a processing component such as the
processing component 316 of FIG. 3A. FIG. 3B does include a
projecting component 396 to project at least some of the
measurements from a first data bin to a second data bin. In some
embodiments, a value describing which data bin the input
measurements 390 belong to may be accepted together with the input
measurements 390. In some embodiments, the data bin may be
determined by the projecting component 396, for example by
analyzing the accepted values. For example, electrical values may
be classified to chaotic rhythms and sinusoidal rhythms by
algorithms known in the field, for example, as described in the
article titled "A real-time atrial fibrillation detection algorithm
based on the instantaneous state of heart rate", PLoS ONE 10(9)
e0136544, the contents of which is incorporated herein by
reference.
[0325] The system 391 optionally includes one or more measurement
component(s) 392 for collecting measurements 390 from a patient's
body. Measurement components 392 may include, for example,
measurement components such as described above with reference to
FIG. 3A.
[0326] In some embodiments, the measurement component(s) 392 may
not be part of the system 391, and the measurements may be
otherwise provided to the system 391, e.g. through one or more
interfaces connecting external measurement components to a
projecting component 320.
[0327] An output 394 of the measurement component(s) 392 is
optionally a signal and/or digital data as described above with
reference to the output 314 of FIG. 3A.
[0328] The output 394 optionally serves as input to a processing
component 396 which may be, for example, a computer or a central
processing unit.
[0329] Reference is now made to FIG. 3C, which is a simplified
block diagram illustration of a system for imaging an anatomical
structure based on electrical readings according to some
embodiments of the invention.
[0330] FIG. 3C shows components in a system 330 constructed
according to an exemplary embodiment of the invention.
[0331] The system 330 optionally includes:
[0332] a data input component 332 for receiving electrical readings
331 from a plurality of electrodes (not shown);
[0333] an optional pre-processing component 334 for converting
output 333 from the data input component 332 to data points
335;
[0334] a classifying component 336 for classifying each one of the
data points as belonging to one of a plurality of data bins,
producing classified data point 337;
[0335] an identifying component 338 for identifying correspondence
of a set of classified data points 337 in at least a first data bin
and a second data bin of the plurality of data bins;
[0336] a projecting component 340 for projecting data points in the
second data bin to data points in the first data bin using a
transformation;
[0337] a combining component 342 for producing a combined set of
data points 343 comprising the data points of the first data bin
and the projected data points from the second data bin; and
[0338] an optional imaging component 344 for imaging the combined
set of data points.
[0339] The data input component 332 may include electrodes and/or
sensors as described herein, optionally in or on an intra-body
probe.
[0340] The optional pre-processing component 334 may include a
circuit for converting output 333 from the data input component 332
to the data points 335. In some embodiments the optional processing
circuit may be a simple circuit for converting an electric reading
such as current to a dielectric value such as resistivity, or other
electric readings to dielectric values. In some embodiments the
optional pre-processing component 334 may be a data processor as is
known in the art. In some embodiments the optional pre-processing
component 334 may be a software module operating on a data
processor as is known in the art.
[0341] In some embodiments the optional pre-processing component
334 is used for processing input measurements to data points, not
including the projection of data points from one data bin to
another.
[0342] In some embodiments, the classifying component 336
classifies each one of the data points as belonging to one of a
plurality of data bins, and optionally provides the classified data
point, to the identifying component 354. The identifying component
354 optionally accepts both the data in the data point and the
classification or bin to which the data point belongs, identifies a
set of data points in at least a first data bin as corresponding to
a set of data points in a second data bin of the plurality of data
bins, and provides output 339 of the correspondence of the data
points, for example a list of pairs of data points. Alternatively,
the identifying component provides only indication as to which
points correspond to each other, while the points themselves are
delivered directly from the classifying component to the projecting
component.
[0343] In some embodiments one or more of the processing component
334, the classifying component 336, the identifying component 338,
the projecting component 340 and the combining component 342 may
include or be included in a data processor as is known in the art,
specifically programmed to carry out one or more of the processing,
classifying, projecting, and/or combining. In some embodiments the
one or more of the pre-processing component 334, the classifying
component 336, the identifying component 338, the projecting
component 340 and the combining component 342 may be a software
module operating on a data processor as is known in the art.
[0344] In some embodiments the imaging component 344 may be an
image display, whether a two-dimensional display such as a computer
display screen or a three-dimensional display as is known in the
art.
[0345] FIG. 3C describes an exemplary embodiment which includes an
optional pre-processing component 334 for converting output 333
from the data input component 332. In such an embodiment the data
being classified may be processed electrical readings. For example,
the data measured may be voltage values measured by an electrode,
and the data classified may be resistivity values calculated by
pre-processing component 334 based on the voltage values, and
optionally based on further input or inputs.
[0346] Reference is now made to FIG. 3D, which is a simplified
block diagram illustration of a system for imaging an anatomical
structure based on electrical readings according to some
embodiments of the invention.
[0347] FIG. 3D shows components in a system 348 constructed
according to an exemplary embodiment of the invention.
[0348] The system 348 optionally includes:
[0349] a data input component 350 for receiving data points 349
measured from a plurality of electrodes (not shown);
[0350] a classifying component 352 for classifying each one of the
data points as belonging to one of a plurality of data bins,
producing classified data points 353;
[0351] an identifying component 354 for identifying 355 a set of
corresponding data points in at least a first data bin and a second
data bin of the plurality of data bins;
[0352] a projecting component 356 for projecting data points in the
second data bin to data points in the first data bin using a
transformation;
[0353] a combining component 358 for producing a combined set of
data points 359 comprising the data points of the first data bin
and the projected data points from the second data bin; and
[0354] an imaging component 360 for imaging the combined set of
data points.
[0355] FIG. 3D describes an exemplary embodiment which does not
include a processing component for converting output from the data
input component. In such an embodiment the data being classified
may be electrical readings which do not require additional
processing--by way of a non-limiting example, the data being
classified may be voltage as measured by an electrode.
[0356] Reference is now made to FIG. 3E, which is a simplified
block diagram illustration of a system for imaging an anatomical
structure based on electrical readings according to some
embodiments of the invention.
[0357] FIG. 3E shows components in a system 364 constructed
according to an exemplary embodiment of the invention.
[0358] The system 364 optionally includes:
[0359] a data input component 366 for receiving electrical readings
365 from a plurality of electrodes (not shown);
[0360] a pre-processing component 368 for converting the electrical
readings to data points 369;
[0361] a classifying component 370 for classifying each one of the
data points 369 as belonging to one of a plurality of data
bins;
[0362] a projecting component 372 for projecting data points in a
second data bin to data points in a first data bin using a
transformation;
[0363] a combining component 374 for producing a combined set of
data points 375 comprising the data points of the first data bin
and the projected data points from the second data bin; and
[0364] an image generating component 376 for generating an image of
the combined set of data points.
[0365] FIG. 3E describes an exemplary embodiment which does not
include an identifying component for identifying correspondence
between classified data points. In such an embodiment the data may
be classified as belonging to a specific physiological rhythm, such
as a sinus cardiac rhythm, an atrial fibrillation cardiac rhythm, a
breathing rhythm. In some embodiments the classification of the
data may not affect the projecting from one data bin to another,
and the points may be projected from one bin to the other based on,
for example, time data or location data, without taking into
account a priori correspondence between an identified set of points
in one data bin to an identified set of points in the second data
bin.
[0366] Reference is now made to FIG. 3F, which is a simplified
block diagram illustration of a system for imaging an anatomical
structure based on electrical readings according to some
embodiments of the invention.
[0367] FIG. 3F shows components in a system 378 constructed
according to an exemplary embodiment of the invention.
[0368] The system 378 optionally includes:
[0369] a data input component 380 for receiving data points 379
measured from a plurality of electrodes (not shown);
[0370] a classifying component 382 for classifying each one of the
data points as belonging to one of a plurality of data bins,
producing classified data points 383;
[0371] a projecting component 384 for projecting data points in a
second data bin to data points in a first data bin using a
transformation, producing projected data points 385;
[0372] a combining component 386 for producing a combined set of
data points 387 comprising the data points of the first data bin
and the projected data points from the second data bin; and
[0373] an imaging component 388 for imaging the combined set of
data points.
[0374] FIG. 3F describes an exemplary embodiment which does not
include a pre-processing component for converting output from the
data input component. In such an embodiment the data being
classified may be electrical readings which do not require
additional processing--by way of a non-limiting example, the data
being classified may be voltage as measured by an electrode,
requiring no pre-processing.
[0375] Identifying Corresponding Points in Different Bins
[0376] In some embodiments, transforming data point values from a
first data bin to a second data bin is optionally based on
identifying a set of data points in the first data bin which
correspond to data points in the second data bin, and determining a
transformation which transforms the corresponding points from the
first data bin to the second data bin.
[0377] In some embodiments a transformation uses a Coherent Point
Drift (CPD) method. In some embodiments the transformation uses a
multi-CPD (MCPD) method. A non-limiting example of an MCPD method
is described in above-mentioned article "Registration of Multiple
Temporally Related Point Sets Using a Novel Variant of the Coherent
Point Drift Algorithm: Application to Coronary Tree Matching".
[0378] In some embodiments, the transformation which has been
determined is optionally applied to some or all of the
corresponding data points, calculating transformed values for the
some or all of the data points in the set of corresponding data
points.
[0379] In some embodiments the transformation which has been
determined is optionally applied to some or all of the data points
in the first data bin, whether belonging to the set of
corresponding points or not, calculating transformed values.
[0380] It is noted that when a set of corresponding points in the
two data bins includes a large number of points, for example, the
number of corresponding points is larger than their dimensionality,
the transformation determined is potentially accurate.
[0381] It is noted that when a set of corresponding points in the
two data bins includes a number of points larger than a
dimensionality of the data points, the transformation determined is
potentially accurate.
[0382] Reference is now made to FIG. 4A, which is a simplified
flowchart illustration of a method for producing a model of a body
organ based on electrical readings according to some embodiments of
the invention.
[0383] The method of FIG. 4A includes:
[0384] measuring at least two data sets of a body organ (440);
[0385] determining at least one corresponding data point in each
one of the at least two data sets describing the at least one
dimension of the body organ which is undergoing repetitive changes
(442);
[0386] projecting one of the two data sets into another one of the
two data sets, based on the corresponding data (444).
[0387] In some cases, the repetitive changes in the body organ
potentially cause one or more data points in one of the data sets
to correspond to one or more data points in another of the data
sets. In some cases, the data points correspond regardless of
organ's change in time.
[0388] In some embodiments the correspondence is optionally based
on the corresponding points having been measured at a same location
in space, or at a same time along a cycle of the repetitive
changes.
[0389] By way of a non-limiting example, data measured at a same
time along a heartbeat cycle is optionally projected from the one
data set onto the other data set.
[0390] By way of another non-limiting example, data measured at a
same location in a heart chamber, during a different heartbeat, at
a same time along the heartbeat cycle, is optionally projected from
the one data set onto the other data set.
[0391] By way of another non-limiting example, data measured at a
same location in a heart chamber, during a different heartbeat, not
even at a same time along the heartbeat cycle, is optionally
projected from the one data set onto the other data set.
[0392] Identifying that data are measured at a same location may
involve, in some embodiments, tracking, such as tracking with X-ray
or Ultrasound.
[0393] Reference is now made to FIG. 4B, which is a simplified
flowchart illustration of a method for imaging a patient organ
based on electrical readings according to some embodiments of the
invention.
[0394] The method of FIG. 4B includes:
[0395] receiving measurements from a plurality of electrodes
(420);
[0396] classifying the measurements to a plurality of data bins
(422);
[0397] identifying a set of corresponding data points in at least a
first data bin and a second data bin of the plurality of data bins
(424);
[0398] calculating a transformation from the corresponding data
points in the second data bin to the corresponding data points in
the first data bin (426);
[0399] projecting data points in the second data bin to data points
in the first data bin using the transformation (428);
[0400] producing a combined set of data points comprising the data
points of the first data bin and the projected data points from the
second data bin (430); and
[0401] imaging the combined set of data points (432).
[0402] In some embodiments the transformation is optionally a CPD
or multi-CPD transformation.
[0403] In some embodiments the transformation is temporally
coherent.
[0404] Reference is now made to FIG. 5A, which is a simplified
flowchart illustration of a method for combining gate-projected
data points according to some embodiments of the invention.
[0405] FIG. 5A describes, by way of a non-limiting example,
obtaining data points which are voltage measurements from an
intra-body probe near to and/or inside a patient's heart, and
gate-projecting the data points to a common reference data bin.
[0406] The method of FIG. 5A includes:
[0407] Obtaining data points (V, .theta., .phi.) (302), that is
measuring voltage V or voltages at one or more electrode in the
probe, and determining a value .theta. associated with breathing,
and determining a value .phi. associated with the cardiac rhythm.
The value .theta. optionally includes a length of time from a
beginning of a breathing cycle, and/or a percentage of progression
along the breathing cycle, and/or a type of breathing cycle, such
as long, short, panting, sigh. The value .phi. optionally includes
a length of time from a beginning of a cardiac cycle, and/or a
percentage of progression along the cardiac cycle, and/or a type of
cardiac cycle, such as chaotic, atrial fibrillation, regular,
clear, unclear, and/or a phase of the cardiac cycle such a P, Q, R,
S, T.
[0408] Calculating (R, .theta., .phi.) (304), that is, calculating
a location R, which may be a one, two or three dimensional
location, for the data points. The calculation is described by the
following transformation:
V .function. ( .theta. , .phi. ) .fwdarw. f R .function. ( .theta.
, .phi. ) . ##EQU00005##
[0409] In some embodiments the calculation f is optionally done by
methods described in above-referenced PCT Application WO
2018/130974, for example methods named multidimensional scaling
(MDS) and/or spatial coherence, optionally done by methods named
Coherent Point Drift (CPD), or multi-CPD (MCPD), which impose
spatial coherence on (R, .theta., .phi.).
[0410] Calculating (R, .theta..sub.0, .phi.) (306), that is, gate
projecting values of data points from data bins associated with
different .theta. values, to a common reference, or from a first
data bin of a first .theta. value to a second data bin, of a second
.theta. value, .theta..sub.0. Optionally, data bins associated with
multiple different .theta. values are gate projected to the same
.theta..sub.0 data bin. For example, the data bin associated with
the value .theta..sub.0 may be a master-bin. The calculation, or
gate projection, from one bin .theta. to the master-bin
.theta..sub.0 is described by the following transformation:
R .function. ( .theta. , .phi. ) .fwdarw. g R .function. ( .theta.
0 , .phi. ) . ##EQU00006##
[0411] In some embodiments the transformation g is optionally
spatial coherent, and may be found by a Coherent Point Drift (CPD)
algorithm, or a multi-CPD (MCPD) algorithm.
[0412] Calculating (R, .theta..sub.0, .phi..sub.0) (308), that is,
gate projecting values of data points from data bins associated
with different .phi. values, to a common reference, or from a first
data bin of a first .phi. value to a second data bin, of a second
.phi. value, .phi..sub.0. The calculation, or gate projection, from
one bin .phi. to the master-bin .phi..sub.0 is described by the
following transformation:
R .function. ( .theta. , .phi. ) .fwdarw. h R .function. ( .theta.
, .phi. 0 ) . ##EQU00007##
[0413] In some embodiments the transformation h is optionally
spatial coherent, and may be found by a Coherent Point Drift (CPD)
algorithm, or a multi-CPD (MCPD) algorithm.
[0414] Following the above-mentioned gate-projections data points
from additional data bins are optionally used to produce an image R
of the patient's heart. By way of a non-limiting example, before
gate projection, data points from a data bin "0" (which may be a
master-bin) could have been used to produce an image R.sub.0, and
following the gate-projection, data points which did not originally
occur in data bin "0" are combined by gate-projection onto a set of
data points used to produce a new image R.sub.0.
[0415] In some embodiments the method of FIG. 5A is applied only
for a normal rhythm of a heart, that is, for example, non-chaotic,
and/or not during atrial fibrillation.
[0416] It is noted that though the method above is described in
relation to breathing and cardiac beating gate projections, in some
embodiments, gate projection may optionally be performed solely for
breathing or solely for beating.
[0417] An Example Method of Obtaining a g or an h Function
[0418] After calculating (R, f, .phi.) (304), the following R
clouds are obtained: R.sub.1, R.sub.2, . . . R.sub.N, where N is a
number of data bins.
[0419] In the following description the g function is described,
and a similar description is intended to apply to the h function
described above.
[0420] A g function is optionally calculated for each R cloud:
g.sub.i: Ri.fwdarw.R.sub.0, where R.sub.0 may be an optionally
arbitrary selection of a data bin "0", also referred to herein as a
master-bin.
[0421] In some embodiments the g functions are optionally
calculated by multi-CPD (`MCPD`), to find a sequence of
transformations that is temporally coherent.
[0422] In some embodiments the g function is optionally calculated
by multi-CPD so that the g.sub.i functions of temporally
neighboring data bins be similar, close to each other, smoothly
changing. Reference is now made to FIG. 5B, which is a simplified
flowchart illustration of a method for combining gate-projected
data points to produce a combined image according to some
embodiments of the invention.
[0423] FIG. 5B describes in words rather than mathematical symbols,
obtaining data points which are voltage measurements from an
intra-body probe near to and/or inside a patient's heart, and
gate-projecting the data points to a common reference data bin.
[0424] The method of FIG. 5B includes:
[0425] obtaining data points (402);
[0426] producing data sets for each data bin (404);
[0427] performing gate projection to account for breathing
(406);
[0428] performing gate projection to account for cardiac rhythm
(408);
[0429] using a combined data set including gate-projected values to
produce a combined image (410).
[0430] Additional non-limiting example methods are further
described below.
[0431] Reference is now made to FIG. 6A, which is a simplified
flowchart of a method for imaging an anatomical structure based on
electrical readings according to an exemplary embodiment of the
invention.
[0432] The method of FIG. 6A includes:
[0433] receiving electrical readings from a plurality of electrodes
(602);
[0434] converting the electrical readings to data points (603);
[0435] classifying each one of the data points as belonging to one
of a plurality of data bins (604);
[0436] identifying a set of corresponding data points in at least a
first data bin and a second data bin of the plurality of data bins
(605);
[0437] projecting data points in the second data bin to data points
in the first data bin using a transformation (606);
[0438] producing a combined set of data points comprising the data
points of the first data bin and the projected data points from the
second data bin (607); and
[0439] imaging the combined set of data points (608).
[0440] Reference is now made to FIG. 6B, which is a simplified
flowchart of a method for imaging an anatomical structure based on
electrical readings according to an exemplary embodiment of the
invention.
[0441] The method of FIG. 6B includes:
[0442] receiving data points measured from a plurality of
electrodes (612);
[0443] classifying each one of the data points as belonging to one
of a plurality of data bins (613);
[0444] identifying a set of corresponding data points in at least a
first data bin and a second data bin of the plurality of data bins
(614);
[0445] projecting data points in the second data bin to data points
in the first data bin using a transformation (615);
[0446] producing a combined set of data points comprising the data
points of the first data bin and the projected data points from the
second data bin (616); and
[0447] imaging the combined set of data points (617).
[0448] Reference is now made to FIG. 6C, which is a simplified
flowchart of a method for imaging an anatomical structure based on
electrical readings according to an exemplary embodiment of the
invention.
[0449] The method of FIG. 6C includes:
[0450] receiving electrical readings from a plurality of electrodes
(622);
[0451] converting the electrical readings to data points (623);
[0452] classifying each one of the data points to as belonging to
one of a plurality of data bins (624);
[0453] projecting data points in a second data bin to data points
in a first data bin using a transformation (625);
[0454] producing a combined set of data points comprising the data
points of the first data bin and the projected data points from the
second data bin (626); and
[0455] imaging the combined set of data points (627).
[0456] Reference is now made to FIG. 6D, which is a simplified
flowchart of a method for imaging an anatomical structure based on
electrical readings according to an exemplary embodiments of the
invention.
[0457] The method of FIG. 6D includes:
[0458] receiving data points measured from a plurality of
electrodes (632);
[0459] classifying each one of the data points to as belonging to
one of a plurality of data bins (633);
[0460] projecting data points in a second data bin to data points
in a first data bin using a transformation (634);
[0461] producing a combined set of data points comprising the data
points of the first data bin and the projected data points from the
second data bin (635); and
[0462] imaging the combined set of data points (636).
[0463] Classifying Data into Data Bins
[0464] In some embodiments, data points are optionally classified
into data bins according to types of cardiac and/or respiratory
cycles, according to a phase within a cardiac cycle, and optionally
further classified in the time domain. For example, data points
measured during a P segment of heartbeat may be binned in some
embodiments into four bins, for example, data measured during the
first quarter of a duration of the P segment may be classified into
a first bin, data measured during the second quarter may be
classified into a second bin, etc. Some non-limiting examples of
data bins based on types of cardiac cycles include sinus rhythm,
atrial fibrillation, ventricular fibrillation, arrhythmia, and so
on. Some non-limiting examples of types of breathing cycles include
breathing at rest, breathing under stress, shallow breathing, deep
breathing, and so on.
[0465] In some embodiments the time domain data bins may overlap.
For example the time domain may be divided into several data bins,
in the overlapping ranges of 0-20%, 10-30%, 20-40%, etc.
[0466] In some embodiments the time domain data bins may be unequal
in length, regardless if they overlap or not. For example the time
domain may be divided into 7 data bins, in the ranges of 0-20%,
20-40%, 40-50%, 50-60%, 60-70% and 80-90%, and 90-100%.
[0467] In some embodiments the time domain data bins may be both
overlapping and unequal in length.
[0468] In some embodiments the time domain data bins may be both
overlapping and unequal in length.
[0469] In some embodiments classifying data bins is optionally
based on distinguishing between rhythm states. In some embodiments,
the distinguishing is optionally performed by distinguishing
between sinusoidal and chaotic heartbeats, as described in the
above-mentioned article titled "A real-time atrial fibrillation
detection algorithm based on the instantaneous state of heart
rate", PLoS ONE 10(9) e0136544er.
[0470] In some embodiments classifying data bins is based on
distinguishing between various sinusoidal beats (e.g., 80 BPS and
70 BPS), by way of a non-limiting example by using a hidden Markov
model.
[0471] In some embodiments, the above two methods are combined, for
example, by first distinguishing between sinusoidal and chaotic
rhythms, and then distinguishing, within the sinusoidal rhythm,
between different heartbeat rates.
[0472] Correspondence Between Data Bins
[0473] In some embodiments the data bins optionally correspond to
physiological states of an anatomical structure. In some
embodiments, such a state is optionally described by an average
value of specific data in the data bin, and/or a standard deviation
of the specific data.
[0474] In some embodiments, the transformation is performed in
series. Optionally, a transformation taking into account a type of
cardiac rhythm (sinus, arrhythmia, fibrillation and so on as
described elsewhere herein) is performed, optionally followed by a
transformation taking into account a phase in the respiratory
rhythm, optionally followed by a transformation taking into account
a phase in the cardiac correspondence. By way of a non-limiting
example, data gathered under one rhythm is optionally projected
into data gathered under a different rhythm--for example, a map
that was acquired during atrial fibrillation is optionally
projected into another map that was acquired during a sinusoidal
rhythm.
[0475] In some embodiments a transformation may be decomposed to
(or generated as) a sum of N individual transformation functions,
each characterized by a different spatial frequency.
[0476] In some embodiments, especially when N is a large number,
for example above 1,000 points, the transformation is a sum of n
transformations (where n<N). In some embodiments the number n of
functions used to generate the transformation is low relative to N,
for example x=3, 5, 10, 20, 50, or 100. Such a combined transfer
function is typically sufficient to provide a good and smooth
result.
[0477] In some embodiments, the transformation from one bin to
another may be simplified by generating a transformation that has
only low-frequency components. Such a simplified transformation may
result in relatively smooth images, which has low tendency to
follow noise in the data, and low capability to follow small
details in the structure that the data represents. For example, in
some embodiments, a transformation configured to transform N points
(e.g., 1000 or more) is represented as a sum of N components,
characterized by different spatial frequencies (optionally, by N
different spatial frequencies). Out of these components, only the n
ones characterized by the lowest frequencies, are used for
transforming data, and the rest--discarded. In some embodiments, n
is between about 10% and about 20% of N, for example, 1000 points
may be transformed with a transformation made of between 100 and
200 components. In some embodiments, the number of components, or
its ratio to the number of points, may be predetermined. In some
embodiments, a cost function may be used for finding
transformations with only low-frequency components, for example, by
penalizing high-frequency components.
[0478] In some embodiments, the transformation of data from one bin
to another may be constrained to by applying a "penalty" to the
various components of the displacement: the higher the spatial
frequency of a component, the larger is the penalty to its
contribution. Once a displacement W that minimizes the overall
penalty (e.g., a sum, optionally a weighted sum, of the penalty for
misfit and the penalty for high spatial frequencies) is obtained,
it may be used to displace transform points from the source bin to
a target bin Finding a transformation that minimizes the penalty
may be carried out using standard minimization procedures.
[0479] In some embodiments, a canonical state (also referred to as
a base state or a master state or a base rhythm) is optionally
defined as one of the rhythm states (e.g. normal, AF, VF, etc.),
and images from other rhythms are projected onto the canonical
state. Such a projection may be conceptually similar to having a
master image, and projecting other images onto the master image.
Projecting other rhythms onto a canonical rhythm is most effective
when there is a lot of data measured during each rhythm state, so
that a meaningful registration may be obtained despite of
substantial differences between the structure of the body part in
the canonical state, and said structure in states projected on the
canonical state.
[0480] In some embodiments an output of each step of the
transformation is a projected base rhythm, with a transformed base
respiration and a transformed dominant beat, within each one of
which are non-base rhythms projected into the normal rhythm; the
abnormal respiratory breaths projected into the normal breaths; and
the abnormal cardiac beats projected into the normal cardiac
beats.
[0481] In some embodiments, within each of the normal breath phases
and the normal heart beat phases, projection is further performed
using a correspondence between the phase data bins of each signal
into a base rhythm data bin.
[0482] Reference is now made to FIG. 7A, which is a graph 500
showing an example effect of gate-projection on data points
according to some embodiments of the invention.
[0483] FIG. 7A shows values of data points collected over time, and
values of gate-projected data points.
[0484] FIG. 7A shows a first dotted line 503 showing values of data
points collected along an X-axis 501 of time, in seconds, and a
location of the data points along a Y-axis 502, in millimeters,
which corresponds to locations of the points in space, similar to
the values R described with reference to FIG. 5A.
[0485] FIG. 7A also shows a second, solid line 504 showing
transformed, or gate-projected, Y values of the same data points
after gate-projection.
[0486] FIG. 7A shows an example of R data values, measured along
the Y-axis 502 before gate projection (503) and after gate
projection (504).
[0487] As mentioned above, in some embodiments the methods
described with reference to the system of FIGS. 3A-3E are applied
only for a normal rhythm of a heart, that is, for example,
non-chaotic, and/or not during atrial fibrillation.
[0488] In some embodiment gate projection is optionally performed
between different rhythmus heartbeat rhythms .rho.. In some
embodiments gate projection is optionally used to compensate for
movement of an image or a model of a heart between different
rhythms of a heartbeat of a patient, for example when transiting
from standard rhythm (SR), or "normal rhythmus", to atrial
fibrillation (AF), for example by applying a function g.sub.i or
h.sub.i from AF to SR.
[0489] Reference is now made to FIG. 7B, which is a graph showing a
normal cardiac rhythm and an abnormal cardiac rhythm differentiated
according to some embodiments of the invention.
[0490] FIG. 7B shows a duration of each heartbeat cycle along a
Y-axis 512, in seconds, and a progression of time at which the
heartbeat cycle was measured, as a frame number in a series of
time-sequential frames.
[0491] A first set of data points 514 is shown as having a normal
cardiac cycle of 1.24+/-0.02 seconds.
[0492] A second set of data points 513 is shown as having an
abnormal cardiac cycle of 1.02+/-0.29 seconds.
[0493] In some embodiments, a heartbeat is determined to belong in
an abnormal data bin if the heartbeat duration is longer than a
normal and/or average heartbeat duration by an amount greater than
a threshold value in seconds, and/or in percentage, of normal
heartbeat duration.
[0494] In some embodiments a normal rhythmus is optionally
determined by Markov methods from the data, for example, using
Hidden Markov Models.
[0495] HMM (Hidden Markov Models) are statistical models that
describe a time series by a set of unobserved states, where each
state has a probability distribution (e.g., Normal distribution)
over the observed output. The model is defined by these
distributions and by the transition probability from one state to
another.
[0496] In some embodiments the normal rhythm is optionally
calculated based on the observed sequence of outputs, for example
R-R (peak-to-peak period of cardiac rhythm) and/or B-B
(peak-to-peak period of breathing rhythm).
[0497] For patients that experience extreme AF, data may not be
acquired for a normal rhythm and data is acquired and used only
from AF cycles.
[0498] A non-limiting example of multi-modality imaging using
intra-body probe-detected data is now provided. The example is
suited for using gate-projection as described herein to improve the
imaging by using more data points per image and/or by filling in
missing data from an image produced by one data bin with data from
a transformed, gate-projected set of values from another data
bin.
[0499] Reference is now made to FIG. 8, which is a simplified line
drawing illustration of methods of gathering position-identifying
information using intra-body probes according to some embodiments
of the invention.
[0500] FIG. 8 shows intra-body probes 11A, 11B, 11C, within a body
cavity, according to some exemplary embodiments of the present
disclosure. The probes shown may be indicative of different types
of data gathering, and do not necessarily imply simultaneous
positioning of all the probes.
[0501] In some exemplary embodiments an intra-body probe is
optionally introduced into a body, and into a body part or to a
vicinity of a body part. The intra-body probe is optionally used to
produce various measurements, such as electrical measurement,
and/or other measurement described herein.
[0502] In some embodiments a location of the intra-body probe is
optionally tracked using a tracking system dedicated to the
tracking.
[0503] In some embodiments a location of the intra-body probe is
tracked by analyzing signals received by the intra-body probe.
[0504] Probes 11A, 11B, 11C are shown in a volume 600 to be mapped,
to illustrate acquisition of data, which can be used to assist in
refining and/or constructing a model. The probes may acquire data
using different modalities of data acquisition, such as measuring
electric potential, electric current, temperature, pH, and so
on.
[0505] Probe 11A is shown in an act of measuring endogenous
electrical activity 63 in a region of heart atrium wall tissue 50.
Optionally, in some embodiments, measured electrical activity
(e.g., an electrogram) is used as an indicator of position of a
probe, for example, based on a phase delay with which activity is
measured at a particular position, compared to some landmark phase,
such as the QRS complex of an electrocardiogram (ECG). Optionally,
the phase difference is measured relative to a non-contacting
electrode on probe 11A itself (for example, a ring electrode),
which potentially helps to cancel surrounding noise. This phase
delay is optionally treated as creating a data dimension applicable
across a surface of a heart. In some embodiments, such a probe 11A
potentially produces measurement data (electrical activity) which
can be used to calculate a time relative to a start of the cardiac
rhythm, or a phase within the cardiac rhythm.
[0506] Probe 11B is shown partially exploring the interior of a
root of pulmonary vein 48. Different tissue structures have been
found to display noticeably different impedance behaviors which can
be gathered by electrodes of an intra-body probe and distinguished
through analysis, for example, by a dielectric property analyzer,
optionally in communication via an electromagnetic field
generator/measurer used to operate electrodes on the probe(s). In
particular, in some embodiments of the invention, positions within
veins and within heart atria are optionally distinguished according
to their impedance properties with positions in veins, for example,
having a relatively higher impedance value. In some embodiments,
such a probe 11B potentially produces measurement data (electrical
activity) which can be analyzed to determine a dielectric property
such as impedance, which can be used to estimate a position of the
probe, for example as a position at an atrial wall, characterized
by an impedance strictly different than the atrial blood pool.
[0507] In some embodiments, distinguishable dielectric properties
of tissue itself are optionally used as a landmark. Tissue
dielectric properties are optionally measured, for example, as
described in PCT patent application publication number WO
2016/181316 titled "Contact Quality Assessment by Dielectric
Property Analysis", the contents of which are incorporated herein
by reference in their entirety. Transitions between two tissue
types (and/or any other impedance change landmarks, for example due
to tissue wall thickness, scarring, ablation, edema, and the like)
are optionally used to register a voltage/spatial mapping to a more
accurately determined size. Additionally or alternatively, such
landmarks optionally serve in re-identification of tissue positions
in case of changes to an electromagnetic field-based frame of
reference.
[0508] It is noted that such use of landmarks comprises mapping
relative to contact with identified structural features of interest
directly, as distinguished from mapping relative to
spatially-defined coordinates (at which structural features are
supposed to exist). Potentially, this is particularly useful when
navigation targets such as in heart atrial wall are in continuous
movement relative to spatially-defined coordinates. Optionally,
both types of information are used together: for example, a spatial
coordinate system is established by measurements of voltages in a
spatially distributed electromagnetic fields, and tissue landmarks
identified by contact measurements from a probe are assigned
coordinates as they are encountered.
[0509] Probe 11C is shown in contact with a general region 62 of
atrium wall tissue 50, that is, a region which is not particularly
singled out as a landmark. The inventors have found that it is
possible, in some embodiments, to detect an anterior-posterior
gradient in the size of voltage fluctuations while in contact with
atrial heart wall tissue, due to relatively greater anterior
movement as a result of heart contraction. Optionally, this
fluctuation gradient itself serves as another part of a frame of
reference for defining positions in contact with the heart
wall.
[0510] In some embodiments of the invention, apart from one or more
of the various sensing modalities described herein, a position of
an intra-body probe, optionally including electrodes thereon, in a
spatial frame of reference is constrained by one or more mechanical
and/or geometrical considerations. For example, the range of
possible positions and/or orientations of a probe known to have
entered a region of tissue from a particular entrance point (a
vein, artery, or fossa, for example) is optionally reduced to a
plausible subset from all possible positions and/or orientations.
Mechanical constraints on probe shape may also be used in position
determinations.
[0511] A non-limiting example of other modalities for obtaining
voltage/spatial mapping information is now provided.
[0512] Apart from probe-measured sources, other sources of
information useful for establishing and/or refining voltage/spatial
mapping are available in some embodiments of the invention. It
should be understood that these methods of voltage/spatial mapping
can optionally be used jointly with the example of multi-modality
imaging using intra-body probe-detected data described above, for
example to provide initial anatomical maps and/or to refine a
voltage/spatial mapping provided by the example described above. A
combination of techniques can be arranged, for example, by use of a
merging algorithm which provides suitable weights to various data
sources.
[0513] To begin with, anatomical data is optionally sourced from
3-D medical images of the patient and/or from anatomical atlas
data. Optionally, geometrical anatomical landmarks expected from
the anatomical data are identified by moving a probe within a
patient until the probe encounters identifiable landmarks, and
registering voltages to spatial positions according to a
characteristic shape, such as a wall of a sinus or a cavity of a
vein, that is seen in the probe travel. Optionally, an overall
shape of a voltage-sample based construction of a model X is
subjected to a geometrical transformation T to fit an anatomy of a
reference geometry Y derived from anatomical data. The
transformation T(X).apprxeq.Y is optionally described, e.g., by the
parameters of an optimal fit of an affine transformation.
Additionally or alternatively, in some embodiments, the
transformation is based on a mapping of corresponding landmarks in
X and Y; i.e. the transformation T is found by matching landmark
sets in the voltage sample-based construction of a model X* with
corresponding geometrically located landmarks Y* to find
T(X*).apprxeq.Y*.
[0514] Anatomical data can also provide simple constraints to
voltage/spatial mapping, for example, by showing in what general
region a heart chamber falls compared to the positions of body
surface electrodes.
[0515] Optionally, anatomical data may be used for constructing
more detailed electromagnetic field simulation data; for example,
as described in International Patent Application No. PCT
IB2016/052692, filed May 11, 2016 and titled FIDUCIAL MARKING FOR
IMAGE-ELECTROMAGNETIC FIELD REGISTRATION, the contents of which are
incorporated herein by reference in their entirety. The more
detailed electromagnetic field simulation data are optionally used
to provide a starting point to assign initial positions of
intra-body probe voltage samples. Alternatively or additionally,
the more detailed electromagnetic field simulation data may be used
as a post-construction constraint (for example, a criterion which
can optionally exclude erroneous measurement values).
[0516] Reference is now made to FIG. 10A, which is a flowchart
illustration of a method of generating an image of a body part
according to an exemplary embodiment of the invention.
[0517] The image to be generated is a combined image, generated
based on a sequence of three or more images of a same body part.
The images may overlap partially or wholly. The images may be
obtained, for example, from measurements made by an intra-body
probe that moves in respect to the body part. For example, the body
part may be a blood vessel along which the probe travels. In
another example, the body part may be a heart chamber, and the
probe may be inside the heart chamber, static (e.g., pressed
against a wall of the heart chamber) or roving inside the heart
chamber.
[0518] Each image shows the body part as captured at a different
time, for example, at time differences of less than a second, e.g.,
of 0.05 seconds, 0.1 seconds, 0.2 seconds, 0.5 seconds, 0.7
seconds, 0.8 seconds, etc. Larger time differences, e.g., of 1
second, 2 seconds, 10 seconds, 20 seconds, 30 seconds, etc., are
also possible. Each image captures the body part during a certain
time window. In some embodiments, some of these time windows may
partially overlap, for example, there may be an overlap between the
time windows of each two consecutive images in the sequence. In
some embodiments, the overlap between time windows may be small
(e.g., less than 20% overlap), large (e.g. 80% or more), or
intermediate (e.g., between 20% and 80%). Typically, the larger the
overlap, the more similar are the images to each other, and the
transformations may be easier to find, although a larger number of
images (and transformations) may be required to cover a specific
period of time. In some embodiments, the time at which data of each
time window was taken may be attributed to a certain point in the
window, e.g., the window start, end, middle, etc. A time difference
between such two points (e.g., between the middle of two time
windows) may be referred to as the time difference between the two
time windows.
[0519] In some embodiments, each image in the sequence is
location-based, i.e., it is made of points representing locations.
For example, points in the image may represent locations in space,
for example, locations of anatomical landmarks (e.g., the mitral
valve, a left atrium appendage, etc.) or any other feature in the
body part. In some embodiments, each image in the sequence is
measurement-based, i.e., made of points representing readings of
values other than locations (e.g., voltages read by electrodes on a
probe probing the body part). The readings, however, may be
indicative of locations, so that location-based images may be
generated from the measurement-based images. In some embodiments,
the method may be applied to a sequence of measurement-based
images, and produces a result of a single measurement-based image.
The measurement-based image may be transformed into a
location-based image by any means known in the art. By way of a
non-limiting example, one way to transform measurement-based images
to location-based images is for a case where the measurements are
of voltages measured by electrodes of a probe, when crossing
electromagnetic fields are applied to a body part from outside the
patient's body, described in the above-mentioned PCT Application
WO2018/130974. Alternatively, if the images are received as
measurement-based images, they may be transformed into
location-based images, and the method may be practiced on these
location-based images.
[0520] In some embodiments, the images may be provided as point
clouds. In some such embodiments, the registration may be practiced
on the point clouds, and after a combined point cloud is obtained
from a sequence of point clouds, the combined point cloud may be
reconstructed to obtain another kind of image, for example, an
image of an outer shell of the point cloud. Alternatively, each of
the provided point cloud images may be first reconstructed, e.g.,
into an outer shell image, so the single image is obtained as an
outer shell or any other kind of image, reconstructed from the
point cloud. In both cases, the reconstruction may be using any
reconstruction method known in the art as such, for example, a
pivoting ball algorithm.
[0521] The method of FIG. 10A includes:
[0522] defining a transformation for registering a first image to a
second image (1002);
[0523] using the defined transformation for registering the first
image to the second image (1004); and
[0524] combining the first image with the second image to provide a
single combined image (1006).
[0525] In some embodiments, a sequence of transformations is
defined, in which each image is registered to another one of the
images. The transformations may be of any kind known in the art as
a registration transformation. The transformations may be rigid, or
non-rigid.
[0526] In some embodiments, a specific region is marked on all the
images in the sequence. For example, a fiducial marker may be
attached to a point in the body part, at least during the imaging
process, and thus appear in each of the images in the sequence. The
fiducial marker may be, for example, a catheter tip pressed against
a point in a heart chamber wall. In such embodiments, the
registration transformations may be defined to register the
fiducial marker in all the images to each other.
[0527] In some embodiments, a processor (e.g., processor 316 of
FIG. 3A) may identify an anatomical landmark in the images. In such
embodiments, the registration transformations may be defined to
register the identified landmarks in all the images in the sequence
to each other. In some embodiments such an identified anatomical
region may provide a constraint on an algorithm that searches for
suitable transformations, and thus may potentially shorten the
search, and may improve the quality of the registration achieved.
An exemplary method of automatically identifying landmarks from
voltage readings of an intra-body probe may be found in PCT
Application WO 2018/207128.
[0528] In some embodiments, the transformations are defined to be
temporally coherent. In this context, temporal coherence is a
property of a sequence of transformations. While a single
transformation is considered spatially coherent if it transforms
points that are near each other in a source image (e.g., in one of
the non-master images) to points that are near each other in the
target image (e.g., in the master image); a sequence of
transformations is temporally coherent if the transformation of
points by one transformation is similar to the transformation of
the same point by the following (or preceding) transformation in
the sequence.
[0529] In some embodiments, the sequence of transformations is
temporally coherent. A method for ensuring that a sequence of
transformations is temporally coherent, is by verifying that the
difference between each two sequential transformations provides a
transformation that by itself is spatially coherent.
[0530] In some embodiments, finding a spatially coherent
transformation, e.g., by the above-mentioned CPD algorithm, may
include minimizing a cost function, which includes a penalty for
high frequency components of the transformation. Finding a
temporally coherent sequence of transformations may involve adding
to a cost function a penalty term that penalizes for high
frequencies in transformations, each of the transformations
obtained by subtracting one of the transformations in the sequence
from an adjacent (following or preceding) transformation in the
sequence.
[0531] In some embodiments, a temporally coherent sequence of
transformations is optionally used for registering the images in
the sequence with each other, for example, by registering all the
non-master images with the master image.
[0532] In some embodiments, operation of the transformations may be
interlaced with the definition of the transformations. Optionally,
each transformation (but the first) may be defined to be temporally
coherent with a preceding transformation.
[0533] Reference is now made to FIG. 10B, which is a flowchart
illustration of a method of generating an image of a body part
according to an exemplary embodiment of the invention.
[0534] FIG. 10B illustrates a method of registering multiple images
to a master image.
[0535] An image to be generated is optionally a single combined
image, generated based on a sequence of at least three (but
typically more) partially overlapping images of a same body part.
The partially overlapping images may be obtained, for example, from
measurements made by an intra-body probe that moves in respect to
the body part. For example, the body part may be a blood vessel
along which the probe travels. In another example, the body part
may be a heart chamber, and the probe may be inside the heart
chamber, static (e.g., pressed against a wall of the heart chamber)
or roving inside the heart chamber.
[0536] Each image in the sequence shows the body part as captured
at a different time, for example, at time differences of less than
a second, e.g., of 0.05 seconds, 0.1 seconds, 0.2 seconds, 0.5
seconds, 0.7 seconds, 0.8 seconds, etc. Larger time differences,
e.g., of 1 second, 2 seconds, 10 seconds, 20 seconds, 30 seconds,
etc., are also possible. Each image captures the body part during a
certain time window. In some embodiments, parts of some of these
time windows may overlap, for example, there may be an overlap
between the time windows of each two consecutive images in the
sequence. In some embodiments, the overlap between time windows may
be small (e.g., less than 20% overlap), large (e.g. 80% or more
overlap), or intermediate (e.g., between 20% and 80%). Typically,
the larger the overlap, the more similar are the images to each
other, and the transformations may be easier to find, although a
larger number of images (and transformations) may be required to
cover a specific period of time. In some embodiments, the time at
which data of each time window was taken may be attributed to a
certain point in the window, e.g., the window start, end, middle,
etc. A time difference between such two points (e.g., between the
middle of two time windows) may be referred to as the time
difference between the two time windows.
[0537] In some embodiments, each image in the sequence is
location-based, i.e., it is made of points representing locations.
For example, points in the image may represent locations in space,
for example, locations of anatomical landmarks (e.g., the mitral
valve, a left atrium appendage, etc.) or any other feature in the
body part. In some embodiments, each image in the sequence is
measurement-based, i.e., made of points representing readings of
values other than locations (e.g., voltages read by electrodes on a
probe probing the body part). The readings, however, may be
indicative of locations, so that location-based images may be
generated from the measurement-based images. In some embodiments,
the method may be applied to a sequence of measurement-based
images, and produces a result of a single measurement-based image.
The measurement-based image may be transformed into a
location-based image by any means known in the art. By way of a
non-limiting example, one way to transform measurement-based images
to location-based images is for a case where the measurements are
of voltages measured by electrodes of a probe, when crossing
electromagnetic fields are applied to a body part from outside the
patient's body, described in the above-mentioned PCT Application WO
2018/130974. Alternatively, if the images are received as
measurement-based images, they may be transformed into
location-based images, and the method may be practiced on these
location-based images.
[0538] In some embodiments a number of images in the sequence is at
least three, and usually less than 100, for example, 5, 10, 20, 50,
or any other number between 3 and 100. The images are optionally
ordered in the sequence according to the times of capturing the
images. If movement between the body part and the probe is periodic
(e.g., in case the body part is the heart or a portion thereof, and
the probe is in a beating heart), the images may be ordered
according to the phase in a cardiac cycle, in which they were
captured. For example, an image taken in the middle of a diastolic
phase of a heartbeat may be ordered after an image taken at the
beginning of the diastolic phase of a later heartbeat. In some
embodiments the order by which the images are arranged plays a role
in generating the single, combined, image.
[0539] The method of FIG. 10B includes:
[0540] defining a sequence of transformations for registering
images in the sequence of images to a master image, which is
optionally one of the images in the sequence (1012);
[0541] using the defined sequence of transformations for
registering the images to the master image (1014); and
[0542] combining the registered images with the master image to
provide a combined image (1016).
[0543] In some embodiments, the sequence of transformations is
defined serially. For example, after a first image is registered
with a master image, the first image and the master image are
combined, and a transformation is optionally defined to register
the combined image with a third image, and so on, optionally to the
end of the sequence. In such embodiments, 1012 1014 1016 are
executed again and again, and in each execution one of the images
is added to the previous ones, so as to generate a final single
combined image.
[0544] In 1016, co-registered images (i.e., the original images,
when registered with each other), are combined to provide a single
combined image. In some embodiments it is also possible not to use
all the images, but only some of the co-registered images. The
combining 1016 may be carried out by generating a single set of
points, which includes all the points of the combined images.
[0545] In some embodiments, the transformations in the sequence of
transformations are defined in 1012 to be temporally coherent. As
mentioned above, temporal coherence may be a property of a sequence
of transformations. While a single transformation is considered
spatially coherent if it transforms points that are near each other
in a source image (e.g., in one of the non-master images) to points
that are near each other in the target image (e.g., in the master
image); a sequence of transformations is temporally coherent if the
transformation of points by one transformation is similar to the
transformation of the same point by the following (or preceding)
transformation in the sequence. In this context "similar" may mean
that the two transformations displace the point in about the same
direction and about the same distance, so that a sequence of
temporally coherent transformations displaces the points in time
along substantially smooth trajectories. Optionally or
additionally, a sequence of temporally coherent transformations,
transforms the points of the source image to the points of the
target image along non-crossing (or minimally crossing)
trajectories.
[0546] One method of ensuring that a sequence of transformations is
temporally coherent, includes verifying that the difference between
each two sequential transformations provides a transformation that
by itself is spatially coherent. In some embodiments, each of the
transformations in the sequence is itself spatially coherent, but
this is not sufficient to ensure that the sequence is temporally
coherent.
[0547] In some embodiments, finding a spatially coherent
transformation, e.g., by the above-mentioned CPD algorithm, may
include minimizing a cost function, which includes a penalty for
high frequency components of the transformation. Finding a
temporally coherent sequence of transformations may involve adding
to a cost function a penalty term that penalizes for high
frequencies in transformations, each of which is obtained by
subtracting one of the transformations in the sequence from an
adjacent (following or preceding) transformation in the sequence.
In some embodiments, a temporally coherent sequence of
transformations is optionally used for registering the images in
the sequence with each other, for example, by registering all the
non-master images with the master image.
[0548] Reference is now made to FIG. 11A, which is a simplified
flowchart illustration of a method for combining N images into one,
according to an exemplary embodiment of the invention.
[0549] FIG. 11A is a flowchart showing steps in a serial execution
of the methods described above, and FIG. 11B is a flowchart showing
steps in parallel execution of the methods. Both flow charts begin
with receiving N images.
[0550] The method of FIG. 11A includes:
[0551] receiving N images (1102);
[0552] setting a counter i to an initial value, for example i=1
(1104);
[0553] defining a registration of image i to image i+1 (1106);
[0554] performing the registration of image i to image i+1
(1108);
[0555] combining image i with image i+1 (1110), to obtain a new
image i+1; and
[0556] optionally performing additional method steps involved with
management of the method, such as checking whether the counter i
has reached an indication that all the images have been processed
(1112), incrementing the counter and repeating the process with an
additional image (1116), or ending the process (1114).
[0557] In FIG. 11A, a registration transformation is defined from
each image (i) to a following image (i+1) (1106). The registration
is executed (1108), and the obtained registered image is combined
into the following image (1110). After the execution of 1116, a new
image of the sequence is transformed to and combined with the
combined image generated in the preceding execution of 1110.
[0558] It is noted that not all the N images have to be received
before a registration of a first two images be defined and even
performed. The images may be received in parallel to the defining
registration and the combining.
[0559] Reference is now made to FIG. 11B, which is a simplified
flowchart illustration of a method for combining N images into one
according to an exemplary embodiment of the invention.
[0560] The method of FIG. 11B includes:
[0561] receiving N images (1122);
[0562] defining one of the images as a master image (1124);
[0563] defining N-1 registrations from each non-master image to the
master image (1126);
[0564] performing the registrations (1128) by transforming the
non-master images; and
[0565] combining the transformed and master images (1130).
[0566] It is noted that not all the N images have to be received
before one of the received images is defined as a master image. A
master image may be defined among a first few images received, and
even a first image can be defined as a master image. Following the
definition of a master image, registrations of non-master received
images may be defined and even performed. The non-master images may
be received in parallel to the defining registration and the
combining.
[0567] In FIG. 11B, a master image is defined (1124), a
registration transformation is defined from each of the N-1
non-master images to the master image (1126); the defined
transformations are performed (1128) to obtain N-1 images
registered with the master image, and at least some of the
registered images and the master image are combined to a single
combined image (1130).
[0568] In some embodiments, the registration transformations
defined in 1126 are defined as a sequence of temporally coherent
transformations. In such embodiments, it may be advantageous to
know all the images in advance, which may facilitate defining of
the sequence of transformations in parallel. For example, a single
cost function may be defined, with N-1 penalty terms, each
penalizing for spatial incoherence of a difference between two
transformations registering two adjacent images to the master
image.
[0569] In some embodiments, additional N-1 penalty terms may be
used to penalize for spatial incoherence of each of the N-1
transformations from the non-master image to the master-image. In
some embodiments, temporal coherence may be imposed on the sequence
of transformations using other conditions, for example, as describe
in the above-mentioned article titled "Registration of Multiple
Temporally Related Point Sets Using a Novel Variant of the Coherent
Point Drift Algorithm: Application to Coronary Tree Matching".
[0570] Reference is now made to FIG. 11C, which is a simplified
flowchart illustration of a method of generating a combined image
of a body part from a sequence of partially overlapping source
images of the body part according to an exemplary embodiment of the
invention.
[0571] The method of FIG. 11C describes generating a combined image
of a body part from a sequence of partially overlapping source
images of said body part, each of the partially overlapping source
images showing the body part at one of a plurality of different
times, the source images being ordered in the sequence according to
said different times.
[0572] The method of FIG. 11C includes:
[0573] defining a temporally coherent sequence of transformations,
for registering the partially overlapping source images in the
sequence with each other (1140);
[0574] registering the source images to each other using the
defined temporally coherent sequence of transformations, to obtain
co-registered images (1142); and
[0575] combining at least some of the co-registered images into a
combined image (1144).
[0576] Reference is now made to FIG. 12, which is a simplified
flowchart illustration of a method of generating an image from a
stream of data according to an exemplary embodiment of the
invention.
[0577] The method of FIG. 12 includes:
[0578] binning a stream of data into a sequence of bins (1202);
[0579] using the data in each bin to produce a corresponding image,
to obtain a sequence images, each associated with corresponding bin
(1204); and
[0580] combining the images in the sequence obtained in 1204 into a
single, combined, image (1206).
[0581] The method of FIG. 12, in some exemplary embodiments
thereof, describes a method of generating a single combined image
of a moving body part from a stream of measurements, which may be
indicative of structure of partially overlapping portions of the
body part. For example, the measurements may be taken from a probe
(static or moving) that probes the body part as the body part
moves, or from a moving probe, where the body part moves in respect
to the probe, and may be static or moving with respect to an
external reference system.
[0582] The method of FIG. 12, includes binning the stream of
measurements to a sequence of bins (1202); using, the measurements
in each bin to generate an image (1204) of a portion of the body
part, so as to obtain a sequence of images that correspond to the
sequence of bins; and generate a single combined image (1206) from
the sequence of images.
[0583] In some embodiments, a sequence of measurements is binned
(1202), that is, measurements made at different time windows are
associated to different bins. The different time windows optionally
overlap with each other. For example, the stream of measurements
may include one minute of measurements, 100 measurements per
second, each time window may be 1 second long, and each time window
may start 50 msec (i.e., 5 measurements, in the present example)
after the preceding window starts, so that about 90% of these two
windows overlap. The non-overlapping times are the first 50 msec of
the first window, and the last 50 msec of the second window. In
some embodiments, an overlap ratio (O.R) may be defined as
O . R = overlap .times. duration .times. between .times. the
.times. two .times. windows total .times. duration .times. of
.times. the .times. two .times. windows ##EQU00008##
[0584] In some embodiments, the overlap ratio is between about 20%
and about 90%, for example, 30%, 50%, 70%, etc.
[0585] In some embodiments, the binning is based on additional
measurements, e.g., on ECG measurements. For example, when the body
part is the heart, the ECG measurements may associate different
time periods with different stages of a heartbeat, such as with a P
wave, a QRS complex, and a T wave. In some embodiments, a finer
partition of the heartbeat may be used, for example to a P segment,
a PR segment, a QRS complex, an ST segment, and a T segment. Other
ways of dividing a heartbeat to different stages are also possible.
In some embodiments, measurements made during each such heartbeat
stage are treated separately. For example, measurements made during
the PR segment are optionally binned to a first sequence of bins,
and steps 1204 and 1206 are practiced on this sequence of bins
alone, to provide a first single image (say a PR single image).
Then, measurements made during another heartbeat stage (e.g., ST
segment) may be binned to a second sequence of bins, and steps 1204
and 1206 are optionally practiced in this second sequence of bins
alone, to obtain a second single image (say an ST single image).
Then, the two single images may be registered to each other and
combined, e.g., using methods known as such in the field.
[0586] In some embodiments, in step 1204, measurements in each bin
are used to generate an image of a portion of the body part. For
example, the measurements may include voltage measurements at three
different frequencies, and each such triplet of measurements may be
presented as a point in a Cartesian coordinate system, so as to
form a 3D image. In some embodiments, the number of frequencies may
be different (e.g., 2 or 5), and the dimensionality of the image
may be the same as the number of fields measured. In some
embodiments, the measurements may be converted into a
location-based image, for example, as taught in above-mentioned PCT
Application WO 2018/130974. Using the method of PCT Application WO
2018/130974 or some other method, step 1204 produces a sequence of
images, and each image in the sequence corresponds to a respective
one of the bins formed in 1202. In some embodiments the bins are of
overlapping time windows, and the images in the obtained sequence
are of partially overlapping portions of the body part.
[0587] In some embodiments, in 1206 a single combined image is
generated from the sequence of images generated in 1204, for
example, by a method such as described with reference to FIGS. 10A,
10B, 11A, and 11B.
[0588] In some embodiments, the stream of measurements is first
classified into sub-streams, each including measurements taken when
the body part was in a different movement mode, and then the method
described with reference to FIG. 12 is practiced on at least one of
the sub-streams, optionally independently of the other
sub-streams.
[0589] Examples of movement modes of a heart may include sinusoidal
rhythm (which is a normal case) and chaotic rhythm (characteristic
of atrial fibrillations). Different modes of heart rhythms may
optionally be distinguished by analyzing ECG signals, and/or by
analyzing electric signals from an intra-body probe.
[0590] In some embodiments, the binning, the generation of a
sequence of images, and the generation of the single combined image
are performed separately for every group (i.e., movement mode), to
generate for each movement mode a different combined image. These
combined images may then be registered to each other and further
combined.
[0591] Reference is now made to FIG. 13, which is a simplified
flowchart illustration of a method for producing a movie of a
beating heart from a sequence of images of the beating heart
according to an exemplary embodiment of the invention.
[0592] The method of FIG. 13 includes:
[0593] receiving a sequence of images (1302) of a beating
heart;
[0594] generating a movie frame from each image in the sequence
(1304); and
[0595] ordering the movie frames according to the order of the
images in the sequence (1306), thereby generating the movie.
[0596] In some embodiments the method of FIG. 13 describes a method
of generating a movie of a beating heart from a sequence of
partially overlapping images of the beating heart, captured during
different time windows, which may be partially overlapping. The
images in the sequence are ordered in the sequence according to the
times at which they were captured. For example, according to a
certain point in the time window, for example, according to the
starting of the windows, according to the endings, or according to
the middle of the windows.
[0597] The movie is made of a sequence of frames. To show the
movie, the frames are displayed according to their order in the
sequence of frames.
[0598] In some embodiments each frame is based on a sequence of
images, and in some embodiments, it is the same sequence of images
that is a basis for all the frames. In some embodiments, each frame
is generated from the sequence of images according to the method
described in FIG. 11B, optionally, using for each frame a different
one of the images as a master-image.
[0599] In some embodiments the order of each frame in the sequence
of frames is optionally the same as the order of the corresponding
image that is used as a master-image. For example, the first frame
in the movie may be a single combined image generated with the
first image as the master-image, the second frame--based on the
second image as the master-image, etc.
[0600] In some embodiments, the movie may be made for displaying as
an infinite loop, so that the first frame is displayed after each
display of the last frame. At least in these cases, there may be no
significance as to which frame is the first in the sequence, but
the order of the frames may make a difference. For example,
reversing the order of the frames (or the order of displaying the
frames) may result in showing the movie backwards in time.
[0601] In some embodiments, the method of FIG. 13 includes two
steps: generating a single frame for each image in the sequence of
images; and ordering the single frames according to the ordering of
the images in the sequence of images.
Example(s)
[0602] Reference is now made to the following examples, which
together with the above descriptions illustrate some embodiments of
the invention in a non-limiting fashion.
[0603] Reference is now made to FIG. 9, which is an image of a
heart produced following gate projection of several data bins into
one common reference data bin according to some embodiments of the
invention.
[0604] FIG. 9 is a first image 701 of a sequence of frames taken of
a left atrium during a systole.
[0605] The movie (also referred herein as a cine) of which image
701 is a first frame, was made by the method described in FIG. 13,
using the method described by FIG. 11B for generating each frame,
with each frame in the sequence making the movie being generated
with a corresponding image as a master-image.
[0606] Data for producing the cine sequence of image frames, for
example Frame(0), Frame(1), Frame(2), and so on, was captured at
time points referenced, for example, as T.sub.0, T.sub.1, T.sub.2
and so on.
[0607] The data was binned into data bins 0, 1, 2 and so on
associated with the time points T.sub.0, T.sub.1, T.sub.2.
[0608] Each one of the image frames Frame(0), Frame(1), Frame(2)
was produced by gate-projecting data from all the data bins into a
data bin associated with the time point T associated with the image
frame, that is: Frame(0) was produced from data points for T.sub.0
and gate-projected data points from T.sub.1 to T.sub.0 and
gate-projected data points from T.sub.2 to T.sub.0, and so on;
Frame(1) was produced from data points for T.sub.1 and
gate-projected data points from T.sub.0 to T.sub.1 and
gate-projected data points from T.sub.2 to T.sub.1 and so on; and
Frame(2) was produced from data points for T.sub.2 and
gate-projected data points from T.sub.0 to T.sub.2 and
gate-projected data points from T.sub.1 to T.sub.2 and so on.
[0609] It is expected that during the life of a patent maturing
from this application many relevant intra-body probes will be
developed and the scope of the term intra-body probe is intended to
include all such new technologies a priori.
[0610] The terms "comprising", "including", "having" and their
conjugates mean "including but not limited to".
[0611] The term "consisting of" is intended to mean "including and
limited to".
[0612] The term "consisting essentially of" means that the
composition, method or structure may include additional
ingredients, steps and/or parts, but only if the additional
ingredients, steps and/or parts do not materially alter the basic
and novel characteristics of the claimed composition, method or
structure.
[0613] As used herein, the singular form "a", "an" and "the"
include plural references unless the context clearly dictates
otherwise. For example, the term "a unit" or "at least one unit"
may include a plurality of units, including combinations
thereof.
[0614] The words "example" and "exemplary" are used herein to mean
"serving as an example, instance or illustration". Any embodiment
described as an "example" or "exemplary" is not necessarily to be
construed as preferred or advantageous over other embodiments
and/or to exclude the incorporation of features from other
embodiments.
[0615] The word "optionally" is used herein to mean "is provided in
some embodiments and not provided in other embodiments". Any
particular embodiment of the invention may include a plurality of
"optional" features unless such features conflict.
[0616] Throughout this application, various embodiments of this
invention may be presented in a range format. It should be
understood that the description in range format is merely for
convenience and brevity and should not be construed as an
inflexible limitation on the scope of the invention. Accordingly,
the description of a range should be considered to have
specifically disclosed all the possible sub-ranges as well as
individual numerical values within that range. For example,
description of a range such as from 1 to 6 should be considered to
have specifically disclosed sub-ranges such as from 1 to 3, from 1
to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as
well as individual numbers within that range, for example, 1, 2, 3,
4, 5, and 6. This applies regardless of the breadth of the
range.
[0617] Whenever a numerical range is indicated herein, it is meant
to include any cited numeral (fractional or integral) within the
indicated range. The phrases "ranging/ranges between" a first
indicate number and a second indicate number and "ranging/ranges
from" a first indicate number "to" a second indicate number are
used herein interchangeably and are meant to include the first and
second indicated numbers and all the fractional and integral
numerals there-between.
[0618] As used herein the term "method" refers to manners, means,
techniques and procedures for accomplishing a given task including,
but not limited to, those manners, means, techniques and procedures
either known to, or readily developed from known manners, means,
techniques and procedures by practitioners of the chemical,
pharmacological, biological, biochemical and medical arts.
[0619] It is appreciated that certain features of the invention,
which are, for clarity, described in the context of separate
embodiments, may also be provided in combination in a single
embodiment. Conversely, various features of the invention, which
are, for brevity, described in the context of a single embodiment,
may also be provided separately or in any suitable sub-combination
or as suitable in any other described embodiment of the invention.
Certain features described in the context of various embodiments
are not to be considered essential features of those embodiments,
unless the embodiment is inoperative without those elements.
[0620] Although the invention has been described in conjunction
with specific embodiments thereof, it is evident that many
alternatives, modifications and variations will be apparent to
those skilled in the art. Accordingly, it is intended to embrace
all such alternatives, modifications and variations that fall
within the spirit and broad scope of the appended claims.
[0621] It is the intent of the Applicant(s) that all publications,
patents and patent applications referred to in this specification
are to be incorporated in their entirety by reference into the
specification, as if each individual publication, patent or patent
application was specifically and individually noted when referenced
that it is to be incorporated herein by reference. In addition,
citation or identification of any reference in this application
shall not be construed as an admission that such reference is
available as prior art to the present invention. T.sub.0 the extent
that section headings are used, they should not be construed as
necessarily limiting. In addition, any priority document(s) of this
application is/are hereby incorporated herein by reference in
its/their entirety.
* * * * *